Handling of data sets during execution of task routines of multiple languages

ABSTRACT

An apparatus includes a processor to: receive a request to perform a job flow defined in a job flow definition; retrieve the most recent versions of a set of task routines to perform a set of tasks of the job flow; analyze each interface of each task routine by which a data set is input or output during execution to identify dependencies where two task routines exchange a data set, and are written in different programming languages; execute the set of task routines to perform the job flow; in response to identifying such a dependency, convert the data set from a form supported by the programming language of one of the two task routines and into a form supported by the programming language of the other; store one of the forms within a federated area; and transmit a result report output during the performance to a remote device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of, and claims the benefit ofpriority under 35 U.S.C. § 120 to, U.S. patent application Ser. No.16/223,518 filed Dec. 18, 2018; which is a continuation-in-part of, andclaims the benefit of priority under 35 U.S.C. § 120 to, U.S. patentapplication Ser. No. 16/205,424 filed Nov. 30, 2018 (since issued asU.S. Pat. No. 10,346,476); which is a continuation-in-part of, andclaims the benefit of priority under 35 U.S.C. § 120 to, U.S. patentapplication Ser. No. 15/897,723 filed Feb. 15, 2018 (since issued asU.S. Pat. No. 10,331,495); all of which are incorporated herein byreference in their respective entireties for all purposes.

This application is also a continuation-in-part of, and claims thebenefit of priority under 35 U.S.C. § 120 to, U.S. patent applicationSer. No. 16/236,401 filed Dec. 29, 2018; which is a continuation-in-partof, and claims the benefit of priority under 35 U.S.C. § 120 to, U.S.patent application Ser. No. 16/039,745 filed Jul. 19, 2018 (since issuedas U.S. Pat. No. 10,360,069); which is a continuation-in-part of, andclaims the benefit of priority under 35 U.S.C. § 120 to, theaforementioned U.S. patent application Ser. No. 15/897,723 filedFebruary 15; all of which are incorporated herein by reference in theirrespective entireties for all purposes.

U.S. patent application Ser. No. 15/897,723 is a continuation-in-partof, and claims the benefit of priority under 35 U.S.C. § 120 to, U.S.patent application Ser. No. 15/896,613 filed Feb. 14, 2018 (since issuedas U.S. Pat. No. 10,002,029); which is a continuation-in-part of, andclaims the benefit of priority under 35 U.S.C. § 120 to, U.S. patentapplication Ser. No. 15/851,869 filed Dec. 22, 2017 (since issued asU.S. Pat. No. 10,078,710); which is a continuation of, and claims thebenefit of priority under 35 U.S.C. § 120 to, U.S. patent applicationSer. No. 15/613,516 filed Jun. 5, 2017 (since issued as U.S. Pat. No.9,852,013); which is a continuation of, and claims the benefit ofpriority under 35 U.S.C. § 120 to, U.S. patent application Ser. No.15/425,886 filed Feb. 6, 2017 (since issued as U.S. Pat. No. 9,684,544);which is a continuation of, and claims the benefit of priority under 35U.S.C. § 120 to, U.S. patent application Ser. No. 15/425,749 also filedon Feb. 6, 2017 (since issued as U.S. Pat. No. 9,684,543); all of whichare incorporated herein by reference in their respective entireties forall purposes.

This application also claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 62/717,873 filed Aug.12, 2018, and to U.S. Provisional Application Ser. No. 62/801,173 filedFeb. 5, 2019, both of which are incorporated herein by reference intheir respective entireties for all purposes.

U.S. patent application Ser. No. 16/223,518 also claims the benefit ofpriority under 35 U.S.C. § 119(e) to U.S. Provisional Application Ser.No. 62/654,643 filed Apr. 9, 2018, which is incorporated herein byreference in its entirety for all purposes. U.S. patent application Ser.No. 16/205,424 also claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 62/631,462 filed Feb.15, 2018, which is incorporated herein by reference in its entirety forall purposes.

U.S. patent application Ser. No. 16/236,401 also claims the benefit ofpriority under 35 U.S.C. § 119(e) to U.S. Provisional Application Ser.No. 62/689,040 filed Jun. 22, 2018, which is incorporated herein byreference in its entirety for all purposes. U.S. patent application Ser.No. 16/039,745 also claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 62/534,678 filed Jul.19, 2017, and to U.S. Provisional Application Ser. No. 62/560,506 filedSep. 19, 2017, both of which are incorporated herein by reference intheir respective entireties for all purposes.

U.S. patent application Ser. No. 15/896,613 also claims the benefit ofpriority under 35 U.S.C. § 119(e) to U.S. Provisional Application Ser.No. 62/460,000 filed Feb. 16, 2017, which is incorporated herein byreference in its entirety for all purposes. U.S. patent application Ser.No. 15/425,749 also claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 62/292,078 filed Feb. 5,2016, and to U.S. Provisional Application Ser. No. 62/297,454 filed Feb.19, 2016, both of which are incorporated herein by reference in theirrespective entireties for all purposes.

BACKGROUND

Distributed development and execution of task routines using pooled taskroutines with pooled data has advanced to an extent that the addition ofmechanisms for organization of development and to provide oversight forreproducibility and accountability have become increasingly desired. Invarious scientific, technical and other areas, the quantities of dataemployed in performing analysis tasks have become ever larger, therebymaking desirable the pooling of data objects to enable collaboration,share costs and/or improve access. Also, such large quantities of data,by virtue of the amount and detail of the information they contain, havebecome of such value that it has become desirable to find as many usesas possible for such data in peer reviewing and in as wide a variety ofanalysis tasks as possible. Thus, the pooling of components of analysisroutines to enable reuse, oversight and error checking has also becomedesirable.

SUMMARY

This summary is not intended to identify only key or essential featuresof the described subject matter, nor is it intended to be used inisolation to determine the scope of the described subject matter. Thesubject matter should be understood by reference to appropriate portionsof the entire specification of this patent, any or all drawings, andeach claim.

An apparatus includes a processor and a storage to store instructionsthat, when executed by the processor, cause the processor to performoperations including receive, at the processor and from a remote device,a request to perform a job flow defined in a job flow definition storedin at least one federated area, wherein: the job flow definitionspecifies a set of tasks to be performed via execution of acorresponding set of task routines during the job flow performance; atleast one flow input data set is to be employed as an input to the jobflow performance; at least one mid-flow data set is to be exchangedbetween at least two of the set of task routines; at least one resultreport is to be output during the job flow performance; and the at leastone federated area is maintained within at least one storage device tostore the job flow definition, and multiple task routines, data sets andresult reports. The processor is also caused to: retrieve, from amongthe multiple task routines, a most recent version of each task routineof the set of task routines to perform a corresponding task of the setof tasks when executed; analyze each interface of each task routine ofthe set of task routines by which a data set is accepted as an input oris output during execution of the task routine to identify at least onedependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in different programminglanguages; and execute the executable instructions of the set of taskroutines to perform the set of tasks to thereby perform the job flow.The processor is also caused to, in response to having identified atleast one dependency in which the first task routine outputs a mid-flowdata set that the second task routine accepts as an input, and in whichthe first task routine and the second task routine include executableinstructions written in different programming languages, performoperations including, for each identified dependency of the at least oneidentified dependency: convert the mid-flow data set from a first formsupported by the programming language in which the executableinstructions of the first task routine are written, and into a secondform supported by the programming language in which the executableinstructions of the second task routine are written; and store one ofthe first form and the second form of the mid-flow data set within theat least one federated area as one of the multiple data sets. Theprocessor is also caused to transmit the at least one result reportoutput during the performance of the job flow to the remote device.

Alternatively or additionally, a computer-program product tangiblyembodied in a non-transitory machine-readable storage medium includesinstructions operable to cause a processor to perform operationsincluding receive, at the processor and from a remote device, a requestto perform a job flow defined in a job flow definition stored in atleast one federated area, wherein: the job flow definition specifies aset of tasks to be performed via execution of a corresponding set oftask routines during the job flow performance; at least one flow inputdata set is to be employed as an input to the job flow performance; atleast one mid-flow data set is to be exchanged between at least two ofthe set of task routines; at least one result report is to be outputduring the job flow performance; and the at least one federated area ismaintained within at least one storage device to store the job flowdefinition, and multiple task routines, data sets and result reports.The processor is also caused to: retrieve, from among the multiple taskroutines, a most recent version of each task routine of the set of taskroutines to perform a corresponding task of the set of tasks whenexecuted; analyze each interface of each task routine of the set of taskroutines by which a data set is accepted as an input or is output duringexecution of the task routine to identify at least one dependency amongat least two task routines in which a first task routine of the at leasttwo task routines outputs a mid-flow data set that a second task routineof the at least two task routines accepts as an input, and in which thefirst task routine and the second task routine include executableinstructions written in different programming languages; and execute theexecutable instructions of the set of task routines to perform the setof tasks to thereby perform the job flow. The processor is also causedto, in response to having identified at least one dependency in whichthe first task routine outputs a mid-flow data set that the second taskroutine accepts as an input, and in which the first task routine and thesecond task routine include executable instructions written in differentprogramming languages, perform operations including, for each identifieddependency of the at least one identified dependency: convert themid-flow data set from a first form supported by the programminglanguage in which the executable instructions of the first task routineare written, and into a second form supported by the programminglanguage in which the executable instructions of the second task routineare written; and store one of the first form and the second form of themid-flow data set within the at least one federated area as one of themultiple data sets. The processor is also caused to transmit the atleast one result report output during the performance of the job flow tothe remote device.

In a dependency of the at least one identified dependency, a selectedone of the programming language in which the executable instructions ofthe first task routine are written and the programming language in whichthe executable instructions of the second task routine are written maybe designated as a primary programming language, and the non-selectedone may be designated as a secondary programming language; and themultiple data sets and result reports are stored in the at least onefederated area in the one of the first form and the second form that issupported by the primary programming language.

The processor may be caused to analyze each interface of each taskroutine of the set of task routines to identify at least one otherdependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in the same programminglanguage. The processor may also be caused to, in response to havingidentified at least one other dependency in which the first task routineoutputs a mid-flow data set that the second task routine accepts as aninput, and in which the first task routine and the second task routineinclude executable instructions written in the same programminglanguage, perform operations including, for each identified dependencyof the at least one other identified dependency: refrain from convertingthe mid-flow data set between the first form and the second form;analyze the form of the mid-flow data set to determine whether itincludes the one of the first form and the second form that is supportedby the primary programming language; and in response to a determinationthat the form of the mid-flow data set includes the one of the firstform and the second form that is supported by the primary programminglanguage, store the mid-flow data set within the at least one federatedarea as one of the multiple data sets.

In response to having identified at least one dependency in which thefirst task routine outputs a mid-flow data set that the second taskroutine accepts as an input, and in which the first task routine and thesecond task routine include executable instructions written in differentprogramming languages, the processor may be caused to perform operationsincluding: instantiate a shared memory space to store at least onemid-flow data set during the job flow performance; and for eachidentified dependency of the at least one identified dependency: storethe one of the first form and the second form of the mid-flow data setwithin the at least one federated area as one of the multiple data setsbased on which of the first form and the second form is supported by theprimary programming language; and store another of the first form andthe second form of the mid-flow data set that is supported by thesecondary programming language within the shared memory space as themid-flow data set is converted.

One of the primary programming language and the secondary programminglanguage may be selected from a group consisting of: SAS programminglanguage; Python; JSON; Pascal; Fortran; BASIC; C; C++; R; and CUDA.

The conversion of the mid-flow data set for each identified dependencyof the at least one identified dependency may include a conversionselected from a group consisting of: a change between data types; achange between byte orderings; a change between delimiters separatingdata values; a change between big Endian and little Endian; a changebetween byte widths of data values; a change in encoding of data values;a reordering of data values between starting with a highest index valueand starting with a lowest index value; a change between a row-columnorganization and a column-row organization; a serialization fromstructured data to un-structured data; a de-serialization fromunstructured data to structured data; a serialization from an array tocomma-separated variables; and a de-serialization from comma-separatedvariables to an array.

The processor may be caused to perform operations including: for eachtask routine of the set of task routines that includes executableinstructions written in a first programming language, execute a firstruntime interpreter or compiler to execute, by the processor, theexecutable instructions written in the first programming language; andfor each task routine of the set of task routines that includesexecutable instructions written in a second programming language,execute a second runtime interpreter or compiler to execute, by theprocessor, the executable instructions written in the second programminglanguage.

The processor may be caused to perform operations including: receive, atthe processor, a task routine from another device; retrieve a flow taskidentifier from the received task routine that identifies the task thatthe received task routine performs when the executable instructions ofthe received task routine are executed; and analyze each task routine ofthe multiple task routines to identify at least one task routine of themultiple task routines that performs the same task when the executableinstructions of the at least one task routine are executed. Theprocessor may also be caused to, in response to identifying at least oneother task routine of the multiple task routines that performs the sametask, perform operations including: analyze the received task routine toidentify the programming language in which the executable instructionsare written; analyze each task routine of the at least one task routineto identify the programming language in which the executableinstructions of each are written; for the received task routine and foreach task routine of the at least one task routine, select anintermediate translator based on the programming language in which theexecutable instructions are written, and translate a portion of theexecutable instructions that implements the interface into anintermediate representation; compare the intermediate representationsgenerated from the executable instructions of the received task routineand each task routine of the at least one task routine to determine ifthere is a match; and in response to a determination that there is amatch, store the received task routine among the multiple task routinesin the at least one federated area.

The processor may be caused to, in response to a determination thatthere is not a match, perform operations including: generate a directedacyclic graph (DAG) that depicts a difference between the interface ofthe received task routine and the interface of the at least one taskroutine; and transmit the DAG to the other device.

Each intermediate representation may include executable instructionswritten in an intermediate programming language.

A computer-implemented method includes receiving, by a processor, andfrom a remote device, a request to perform a job flow defined in a jobflow definition stored in at least one federated area, wherein: the jobflow definition specifies a set of tasks to be performed via executionof a corresponding set of task routines during the job flow performance;at least one flow input data set is to be employed as an input to thejob flow performance; at least one mid-flow data set is to be exchangedbetween at least two of the set of task routines; at least one resultreport is to be output during the job flow performance; and the at leastone federated area is maintained within at least one storage device tostore the job flow definition, and multiple task routines, data sets andresult reports. The method also includes: retrieving, from among themultiple task routines, a most recent version of each task routine ofthe set of task routines to perform a corresponding task of the set oftasks when executed; analyzing, by the processor, each interface of eachtask routine of the set of task routines by which a data set is acceptedas an input or is output during execution of the task routine toidentify at least one dependency among at least two task routines inwhich a first task routine of the at least two task routines outputs amid-flow data set that a second task routine of the at least two taskroutines accepts as an input, and in which the first task routine andthe second task routine include executable instructions written indifferent programming languages; and executing, by the processor theexecutable instructions of the set of task routines to perform the setof tasks to thereby perform the job flow. The method also includes inresponse to having identified at least one dependency in which the firsttask routine outputs a mid-flow data set that the second task routineaccepts as an input, and in which the first task routine and the secondtask routine include executable instructions written in differentprogramming languages, performing operations including, for eachidentified dependency of the at least one identified dependency:converting, by the processor, the mid-flow data set from a first formsupported by the programming language in which the executableinstructions of the first task routine are written, and into a secondform supported by the programming language in which the executableinstructions of the second task routine are written; and storing one ofthe first form and the second form of the mid-flow data set within theat least one federated area as one of the multiple data sets. The methodalso includes transmitting, from the processor, the at least one resultreport output during the performance of the job flow to the remotedevice.

In a dependency of the at least one identified dependency, a selectedone of the programming language in which the executable instructions ofthe first task routine are written and the programming language in whichthe executable instructions of the second task routine are written maybe designated as a primary programming language, and the non-selectedone may be designated as a secondary programming language; and themultiple data sets and result reports may be stored in the at least onefederated area in the one of the first form and the second form that issupported by the primary programming language.

The method may include, analyzing, by the processor, each interface ofeach task routine of the set of task routines to identify at least oneother dependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in the same programminglanguage. The method may also include, in response to having identifiedat least one other dependency in which the first task routine outputs amid-flow data set that the second task routine accepts as an input, andin which the first task routine and the second task routine includeexecutable instructions written in the same programming language,performing operations including, for each identified dependency of theat least one other identified dependency: refraining from converting themid-flow data set between the first form and the second form; analyzing,by the processor, the form of the mid-flow data set to determine whetherit includes the one of the first form and the second form that issupported by the primary programming language; and in response to adetermination that the form of the mid-flow data set includes the one ofthe first form and the second form that is supported by the primaryprogramming language, storing the mid-flow data set within the at leastone federated area as one of the multiple data sets.

The method may include, in response to having identified at least onedependency in which the first task routine outputs a mid-flow data setthat the second task routine accepts as an input, and in which the firsttask routine and the second task routine include executable instructionswritten in different programming languages, performing operationsincluding: instantiating, by the processor, a shared memory space tostore at least one mid-flow data set during the job flow performance;and for each identified dependency of the at least one identifieddependency: storing the one of the first form and the second form of themid-flow data set within the at least one federated area as one of themultiple data sets based on which of the first form and the second formis supported by the primary programming language; and storing another ofthe first form and the second form of the mid-flow data set that issupported by the secondary programming language within the shared memoryspace as the mid-flow data set is converted.

One of the primary programming language and the secondary programminglanguage may be selected from a group consisting of: SAS programminglanguage; Python; JSON; Pascal; Fortran; BASIC; C; C++; R; and CUDA.

The conversion of the mid-flow data set for each identified dependencyof the at least one identified dependency may include a conversionselected from a group consisting of: a change between data types; achange between byte orderings; a change between delimiters separatingdata values; a change between big Endian and little Endian; a changebetween byte widths of data values; a change in encoding of data values;a reordering of data values between starting with a highest index valueand starting with a lowest index value; a change between a row-columnorganization and a column-row organization; a serialization fromstructured data to un-structured data; a de-serialization fromunstructured data to structured data; a serialization from an array tocomma-separated variables; and a de-serialization from comma-separatedvariables to an array.

The method may include: for each task routine of the set of taskroutines that includes executable instructions written in a firstprogramming language, executing, by the processor, a first runtimeinterpreter or compiler to execute, by the processor, the executableinstructions written in the first programming language; and for eachtask routine of the set of task routines that includes executableinstructions written in a second programming language, executing, by theprocessor, a second runtime interpreter or compiler to execute, by theprocessor, the executable instructions written in the second programminglanguage.

The method may include: receiving, at the processor, a task routine fromanother device; retrieving a flow task identifier from the received taskroutine that identifies the task that the received task routine performswhen the executable instructions of the received task routine areexecuted; and analyzing, by the processor, each task routine of themultiple task routines to identify at least one task routine of themultiple task routines that performs the same task when the executableinstructions of the at least one task routine are executed. The methodmay also include, in response to identifying at least one other taskroutine of the multiple task routines that performs the same task,performing operations including: analyzing, by the processor, thereceived task routine to identify the programming language in which theexecutable instructions are written; analyzing, by the processor, eachtask routine of the at least one task routine to identify theprogramming language in which the executable instructions of each arewritten; for the received task routine and for each task routine of theat least one task routine, selecting, by the processor, an intermediatetranslator based on the programming language in which the executableinstructions are written, and translate a portion of the executableinstructions that implements the interface into an intermediaterepresentation; comparing, by the processor, the intermediaterepresentations generated from the executable instructions of thereceived task routine and each task routine of the at least one taskroutine to determine if there is a match; and in response to adetermination that there is a match, storing the received task routineamong the multiple task routines in the at least one federated area.

The method may include, in response to a determination that there is nota match, performing operations including: generating, by the processor,a directed acyclic graph (DAG) that depicts a difference between theinterface of the received task routine and the interface of the at leastone task routine; and transmitting, from the processor, the DAG to theother device.

Each intermediate representation may include executable instructionswritten in an intermediate programming language.

An apparatus includes a processor and a storage to store instructionsthat, when executed by the processor, cause the processor to performoperations including receive, at the processor, and from a remote devicevia a network, a job flow definition to be stored in a federated area ofat least one federated area, wherein: the job flow definition defines ajob flow as a set of tasks to be performed by execution of acorresponding set of task routines to perform the job flow; the job flowdefinition employs a set of flow task identifiers to identify the set oftasks; and the at least one federated area is maintained within at leastone storage device to store the job flow definition, multiple taskroutines and multiple data sets as objects. The processor is also causedto: retrieve the set of flow task identifies from the job flowdefinition; for each retrieved flow task identifier, retrieve, fromamong the multiple task routines, a most recent version of a taskroutine of the set of task routines that performs the corresponding taskof the set of tasks when executed; translate a portion of executableinstructions within each retrieved task routine of the set of taskroutines that implements an interface by which a data set is accepted asan input or is output during execution of the task routine into anintermediate representation; analyze executable instructions of the jobflow definition to determine whether the executable instructions of thejob flow definition are written in a primary programming language;translate a portion of the executable instructions within the job flowdefinition that defines the interface for each task routine of the setof task routines into an intermediate representation; and compare eachintermediate representation generated from one of the retrieved taskroutines to the corresponding intermediate representation generated fromthe job flow definition to determine if there is a match. The processoris also caused to, in response to a determination that there is a matchfor each comparison of intermediate representations, and in response toa determination that the executable instructions of the job flowdefinition are written in a secondary programming language, performoperations including: translate the portion of the executableinstructions of the job flow definition that defines the interface foreach task routine of the set of task routines into the primaryprogramming language to generate a translated form of the job flowdefinition; and store the translated form of the job flow definitionwithin the federated area.

Alternatively or additionally, a computer-program product tangiblyembodied in a non-transitory machine-readable storage medium includesinstructions operable to cause a processor to perform operationsincluding receive, at the processor, and from a remote device via anetwork, a job flow definition to be stored in a federated area of atleast one federated area, wherein: the job flow definition defines a jobflow as a set of tasks to be performed by execution of a correspondingset of task routines to perform the job flow; the job flow definitionemploys a set of flow task identifiers to identify the set of tasks; andthe at least one federated area is maintained within at least onestorage device to store the job flow definition, multiple task routinesand multiple data sets as objects. The processor is also caused to:retrieve the set of flow task identifies from the job flow definition;for each retrieved flow task identifier, retrieve, from among themultiple task routines, a most recent version of a task routine of theset of task routines that performs the corresponding task of the set oftasks when executed; translate a portion of executable instructionswithin each retrieved task routine of the set of task routines thatimplements an interface by which a data set is accepted as an input oris output during execution of the task routine into an intermediaterepresentation; analyze executable instructions of the job flowdefinition to determine whether the executable instructions of the jobflow definition are written in a primary programming language; translatea portion of the executable instructions within the job flow definitionthat defines the interface for each task routine of the set of taskroutines into an intermediate representation; and compare eachintermediate representation generated from one of the retrieved taskroutines to the corresponding intermediate representation generated fromthe job flow definition to determine if there is a match. The processoris also caused to, in response to a determination that there is a matchfor each comparison of intermediate representations, and in response toa determination that the executable instructions of the job flowdefinition are written in a secondary programming language, performoperations including: translate the portion of the executableinstructions of the job flow definition that defines the interface foreach task routine of the set of task routines into the primaryprogramming language to generate a translated form of the job flowdefinition; and store the translated form of the job flow definitionwithin the federated area.

The processor may be caused to: maintain a first transfer area withinthe federated area; cooperate with the remote device via the network toexchange objects via the network to synchronize objects between thefirst transfer area and a second transfer area maintained by the remotedevice; cooperate with the remote device to receive the job flowdefinition in an exchange of objects via the network to synchronize theobjects between the first transfer area and the second transfer area inresponse to the job flow definition having been stored within the secondtransfer area or in response to the a more recent version of the jobflow definition having been stored within the second transfer area; andin response to a determination that there is a match for each comparisonof intermediate representations, and in response to a determination thatthe executable instructions of the job flow definition are written in asecondary programming language, store the translated form of the jobflow definition within the first transfer area.

The processor may be caused to, in response to a change having been madeto the translated form of the job flow definition stored within thefirst transfer area, perform operations including: reverse-translate theportion of the executable instructions of the changed translated form ofthe job flow definition that defines the interface for each task routineof the set of task routines from the primary programming language intothe secondary programming language to generate a reverse-translated formof the job flow definition; and cooperate with the remote device via thenetwork to transmit the reverse-translated form of the job flowdefinition to the remote device in an exchange of objects via thenetwork to synchronize the objects between the first transfer area andthe second transfer area.

The executable instructions of the job flow definition may include aportion of executable instructions to implement a graphical userinterface (GUI) when executed. In response to a determination that thereis a match for each comparison of intermediate representations, and inresponse to a determination that the executable instructions of the jobflow definition are written in a secondary programming language, theprocessor may be caused to translate the portion of the executableinstructions that implement the GUI from the secondary programminglanguage into GUI instructions within the translated form of the jobflow definition in the primary programming language. In response to achange having been made to the translated form of the job flowdefinition stored within the first transfer area, the processor may becaused to reverse-translate the GUI instructions within the changedtranslated form of the job flow definition into the secondary languagein a corresponding portion of the executable instructions of thereverse-translated form of the job flow definition.

The processor may be caused, in response to a determination that thereis a lack of a match for at least one comparison of intermediaterepresentations, to perform operations including: generate a directedacyclic graph (DAG) that depicts the lack of a match for the at leastone comparison; and transmit the DAG to the remote device.

The first transfer area and the second transfer area may be usedcooperatively to store and exchange objects as part of collaborativedevelopment of a set of objects of the job flow; the processor mayreceive an indication that the job flow definition has been committed tobecome part of a set of objects required to perform the job flow; and inresponse to the receipt of the indication, the processor may cooperatewith the remote device to receive the job flow definition in an exchangeof objects.

The processor may be caused to perform operations including: receive, atthe processor, and from the remote device via the network, securitycredentials from the remote device as the remote device logs into thefederated area as a user; analyze the security credentials to determinewhether the remote device is authorized to log into the federated area;and in response to a determination that the remote device is authorizedto log into the federated area, the processor grants access to thefederated area to the remote device to enable receipt of the job flowdefinition.

The processor may be caused to perform operations including: use the setof flow task identifiers retrieved from the job flow definition tosearch the at least one federated area for at least one task routine toperform each task of the set of tasks; and in response to a lack of atask routine being stored within the one or more federated for at leastone task of the set of tasks, perform operations comprising: generate adirected acyclic graph (DAG) of the job flow definition that identifiesthe at least one task; and transmit the DAG to the remote device.

The translation of the portion of the executable instructions of the jobflow definition that defines the interface for each task routine of theset of task routines into the primary programming language may includetranslating the intermediate expression for the definition of theinterface for each task routine into executable instructions in theprimary programming language.

The intermediate expression may include executable instructionsgenerated in an intermediate programming language; and one of theprimary programming language, the secondary programming language and theintermediate programming language may be selected from a groupconsisting of: SAS programming language; Python; JSON; Pascal; Fortran;BASIC; C; C++; R; and CUDA.

A computer-implemented method includes receiving, by a processor, andfrom a remote device via a network, a job flow definition to be storedin a federated area of at least one federated area, wherein: the jobflow definition defines a job flow as a set of tasks to be performed byexecution of a corresponding set of task routines to perform the jobflow; the job flow definition employs a set of flow task identifiers toidentify the set of tasks; and the at least one federated area ismaintained within at least one storage device to store the job flowdefinition, multiple task routines and multiple data sets as objects.The method also includes: retrieving the set of flow task identifiesfrom the job flow definition; for each retrieved flow task identifier,retrieving, from among the multiple task routines, a most recent versionof a task routine of the set of task routines that performs thecorresponding task of the set of tasks when executed; translating, bythe processor, a portion of executable instructions within eachretrieved task routine of the set of task routines that implements aninterface by which a data set is accepted as an input or is outputduring execution of the task routine into an intermediaterepresentation; analyzing, by the processor, executable instructions ofthe job flow definition to determine whether the executable instructionsof the job flow definition are written in a primary programminglanguage; translating, by the processor, a portion of the executableinstructions within the job flow definition that defines the interfacefor each task routine of the set of task routines into an intermediaterepresentation; and comparing, by the processor, each intermediaterepresentation generated from one of the retrieved task routines to thecorresponding intermediate representation generated from the job flowdefinition to determine if there is a match. The method also includes,in response to a determination that there is a match for each comparisonof intermediate representations, and in response to a determination thatthe executable instructions of the job flow definition are written in asecondary programming language, performing operations including:translating, by the processor, the portion of the executableinstructions of the job flow definition that defines the interface foreach task routine of the set of task routines into the primaryprogramming language to generate a translated form of the job flowdefinition; and storing the translated form of the job flow definitionwithin the federated area.

The method may include: maintaining a first transfer area within thefederated area; cooperating, by the processor, with the remote devicevia the network to exchange objects via the network to synchronizeobjects between the first transfer area and a second transfer areamaintained by the remote device; cooperating, by the processor, with theremote device to receive the job flow definition in an exchange ofobjects via the network to synchronize the objects between the firsttransfer area and the second transfer area in response to the job flowdefinition having been stored within the second transfer area or inresponse to the a more recent version of the job flow definition havingbeen stored within the second transfer area; and in response to adetermination that there is a match for each comparison of intermediaterepresentations, and in response to a determination that the executableinstructions of the job flow definition are written in a secondaryprogramming language, store the translated form of the job flowdefinition within the first transfer area.

The method may include, in response to a change having been made to thetranslated form of the job flow definition stored within the firsttransfer area, performing operations including: reverse-translating, bythe processor, the portion of the executable instructions of the changedtranslated form of the job flow definition that defines the interfacefor each task routine of the set of task routines from the primaryprogramming language into the secondary programming language to generatea reverse-translated form of the job flow definition; and cooperating,by the processor, with the remote device via the network to transmit thereverse-translated form of the job flow definition to the remote devicein an exchange of objects via the network to synchronize the objectsbetween the first transfer area and the second transfer area.

The executable instructions of the job flow definition may include aportion of executable instructions to implement a graphical userinterface (GUI) when executed. The method may include, in response to adetermination that there is a match for each comparison of intermediaterepresentations, and in response to a determination that the executableinstructions of the job flow definition are written in a secondaryprogramming language, translating, by the processor, the portion of theexecutable instructions that implement the GUI from the secondaryprogramming language into GUI instructions within the translated form ofthe job flow definition in the primary programming language. The methodmay include, in response to a change having been made to the translatedform of the job flow definition stored within the first transfer area,reverse-translating, by the processor, the GUI instructions within thechanged translated form of the job flow definition into the secondarylanguage in a corresponding portion of the executable instructions ofthe reverse-translated form of the job flow definition.

The method may include, in response to a determination that there is alack of a match for at least one comparison of intermediaterepresentations, performing operations including: generating, by theprocessor, a directed acyclic graph (DAG) that depicts the lack of amatch for the at least one comparison; and transmitting, from theprocessor, the DAG to the remote device.

The first transfer area and the second transfer area may be usedcooperatively to store and exchange objects as part of collaborativedevelopment of a set of objects of the job flow; the processor mayreceive an indication that the job flow definition has been committed tobecome part of a set of objects required to perform the job flow; andthe method may include, in response to the receipt of the indication,cooperating, by the processor, with the remote device to receive the jobflow definition in an exchange of objects.

The method may include: receiving, at the processor, and from the remotedevice via the network, security credentials from the remote device asthe remote device logs into the federated area as a user; analyzing, bythe processor, the security credentials to determine whether the remotedevice is authorized to log into the federated area; and in response toa determination that the remote device is authorized to log into thefederated area, granting access to the federated area to the remotedevice to enable receipt of the job flow definition.

The method may include: using the set of flow task identifiers retrievedfrom the job flow definition to search the at least one federated areafor at least one task routine to perform each task of the set of tasks;and in response to a lack of a task routine being stored within the oneor more federated for at least one task of the set of tasks, performingoperations including: generating, by the processor, a directed acyclicgraph (DAG) of the job flow definition that identifies the at least onetask; and transmitting, from the processor, the DAG to the remotedevice.

The translation of the portion of the executable instructions of the jobflow definition that defines the interface for each task routine of theset of task routines into the primary programming language may includetranslating the intermediate expression for the definition of theinterface for each task routine into executable instructions in theprimary programming language.

The intermediate expression may include executable instructionsgenerated in an intermediate programming language; and one of theprimary programming language, the secondary programming language and theintermediate programming language may be selected from a groupconsisting of: SAS programming language; Python; JSON; Pascal; Fortran;BASIC; C; C++; R; and CUDA.

The foregoing, together with other features and embodiments, will becomemore apparent upon referring to the following specification, claims, andaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described in conjunction with the appendedfigures:

FIG. 1 illustrates a block diagram that provides an illustration of thehardware components of a computing system, according to some embodimentsof the present technology.

FIG. 2 illustrates an example network including an example set ofdevices communicating with each other over an exchange system and via anetwork, according to some embodiments of the present technology.

FIG. 3 illustrates a representation of a conceptual model of acommunications protocol system, according to some embodiments of thepresent technology.

FIG. 4 illustrates a communications grid computing system including avariety of control and worker nodes, according to some embodiments ofthe present technology.

FIG. 5 illustrates a flow chart showing an example process for adjustinga communications grid or a work project in a communications grid after afailure of a node, according to some embodiments of the presenttechnology.

FIG. 6 illustrates a portion of a communications grid computing systemincluding a control node and a worker node, according to someembodiments of the present technology.

FIG. 7 illustrates a flow chart showing an example process for executinga data analysis or processing project, according to some embodiments ofthe present technology.

FIG. 8 illustrates a block diagram including components of an EventStream Processing Engine (ESPE), according to embodiments of the presenttechnology.

FIG. 9 illustrates a flow chart showing an example process includingoperations performed by an event stream processing engine, according tosome embodiments of the present technology.

FIG. 10 illustrates an ESP system interfacing between a publishingdevice and multiple event subscribing devices, according to embodimentsof the present technology.

FIG. 11 illustrates a flow chart showing an example process ofgenerating and using a machine-learning model according to some aspects.

FIG. 12 illustrates an example machine-learning model based on a neuralnetwork.

FIGS. 13A, 13B, 13C and 13D, together, illustrate an example embodimentof a distributed processing system.

FIGS. 14A and 14B, together, illustrate an example alternate embodimentof a distributed processing system.

FIGS. 15A, 15B, 15C, 15D and 15E, together, illustrate aspects ofexample hierarchical sets of federated areas and their formation.

FIGS. 16A, 16B, 16C, 16D, 16E, 16F, 16G, 16H and 16I, together,illustrate an example of defining and performing a job flow, and ofdocumenting the performance.

FIGS. 17A, 17B, 17C, 17D and 17E, together, illustrate an example ofselectively storing, translating and assigning identifiers to objects infederated area(s).

FIGS. 18A, 18B, 18C, 18D, 18E and 18F, together, illustrate an exampleof organizing, indexing and retrieving objects from federated area(s).

FIGS. 19A, 19B, 19C, 19D and 19E, together, illustrate aspects of thegeneration and use of a DAG.

FIG. 20 illustrates aspects of an example of supporting the use ofobjects written in multiple programming languages in a collaborationamong multiple developers.

FIGS. 21A, 21B, 21C, 21D and 21E, together, illustrate an example ofsupporting the provision of a task routine written in a secondaryprogramming language.

FIGS. 22A, 22B, 22C, 22D and 22E, together, illustrate an example ofsupporting the provision of a job flow definition written in a secondaryprogramming language.

FIGS. 23A, 23B, 23C, 23D, 23E, 23F and 23G, together, illustrate anexample of executing a combination of task routines written in differentprogramming languages.

FIGS. 24A and 24B, together, illustrate an example embodiment of a logicflow of a federated device adding a requested federated area related toone or more other federated areas.

FIGS. 25A, 25B, 25C, 25D, 25E and 25F, together, illustrate an exampleembodiment of a logic flow of a federated device storing objects in afederated area.

FIGS. 26A, 26B and 26C, together, illustrate another example embodimentof a logic flow of a federated device storing objects in a federatedarea

FIGS. 27A, 27B and 27C, together, illustrate still another exampleembodiment of a logic flow of a federated device storing objects in afederated area.

FIGS. 28A, 28B, 28C and 28D, together, illustrate an example embodimentof a logic flow of a federated device deleting objects stored within afederated area.

FIGS. 29A and 29B, together, illustrate an example embodiment of a logicflow of a federated device either repeating an earlier performance of ajob flow that generated specified result report or instance log, ortransmitting objects to enable a requesting device to do so.

FIGS. 30A and 30B, together, illustrate another example embodiment of alogic flow of a federated device repeating an earlier performance of ajob flow.

FIGS. 31A, 31B, 31C and 31D, together, illustrate an example embodimentof a logic flow of a federated device performing a job flow.

FIGS. 32A, 32B, 32C, 32D, 32E, 32F and 32G, together, illustrate anexample embodiment of a logic flow of a federated device executing taskroutines written in a multitude of programming languages.

DETAILED DESCRIPTION

Various embodiments described herein are generally directed totechniques for enabling collaborative development of a set of objectsrequired to define and perform an analysis as a many-task job flow usingdistributed processing where the set of objects may include objectswritten in differing programming languages and/or by developers withdiffering degrees of familiarity with many-task computing. One or morefederated areas may be maintained by federated device(s) to provide aprogramming environment for the development of job flows that implementvarious analyses as a set of tasks to be performed through thedistributed execution of a set of task routines. Such a programmingenvironment may additionally include the use of a primary programminglanguage specifically developed to support such distributed processing.However, while there may be developers who have access to and/or arefamiliar with such a programming environment, including having access toand/or familiarity with the use of the one or more federated areas,those developers may seek to collaborate with other developers who arenot familiar with such a programming environment, are not familiar withthe primary programming language, and/or have not been granted directaccess to the one or more federated areas. Such other developers may berelatively easily guided through dividing an analysis into multipletasks to better fit many-task computing concepts, but may not so easilyadopt the primary programming language. The federated device(s) may becaused to cooperate with another device that serves as a source coderepository to automatically share objects therebetween as those objectsare developed, where the other device provides a different programmingenvironment more familiar to the other developers. The federateddevice(s) may also be caused to automatically translate, into theprimary programming language, a subset of the objects shared by theother device that were created by the other developers in one or moreselected secondary programming languages as part of enabling the otherdevelopers to contribute some of the required objects using theprogramming environment that they are more familiar with. The federateddevice(s) may be further caused to reverse-translate such a subset ofobjects into one of the secondary programming languages as part ofsharing that subset of objects with the other developers through theother device. The federated device(s) may still further be caused toexecute task routines written in both the primary and secondaryprogramming languages, and may automatically perform conversions of thedata types and/or data structures of data objects that are exchangedamong the task routines at runtime to accommodate differences in supportfor data types among the different programming languages, whileminimizing the overall number of such conversions.

The storage of objects (e.g., data objects, task routines, macros oftask routines, job flow definitions, instance logs of past performancesof job flows, and/or DAGs of task routines and/or job flows) may beeffected using a grid of storage devices that are coupled to and/orincorporated into one or more federated devices. The grid of storagedevices may provide distributed storage for data objects that includelarge data sets, complex sets of task routines for the performance ofvarious analyses divided into tasks specified in job flows, and/orinstance logs that document an extensive history of past performances ofsuch analyses. Such distributed storage may be used to provide one orboth of fault tolerance and/or faster access through the use ofparallelism. In various embodiments, the objects stored within afederated area or a set of federated areas may be organized in any of avariety of ways that may employ any of a variety of indexing systems toenable access. By way of example, one or more databases may be definedby the one or more federated devices to improve efficiency in accessingdata objects, task routines and/or instance logs of performances ofanalyses.

The one or more federated devices may define at least some of thestorage space provided by the storage device grid as providing federatedarea(s) in which the objects are stored and to which access iscontrolled by the one or more federated devices (or one or more otherdevices separately providing access control). By way of example, accessto a federated area may be limited to one or more particular authorizedpersons and/or one or more particular authorized entities (e.g.,scholastic entities, governmental entities, business entities, etc.).Alternatively or additionally, access to a federated area may be limitedto one or more particular authorized devices that may be operated underthe control of one or more particular persons and/or entities.

In various embodiments, the manner in which a federated area is used maybe limited to the storage and retrieval of objects with controlledaccess, while in other embodiments, the manner in which a federated areais used may additionally include the performances of analyses as jobflows using the objects stored therein. In support of enabling at leastthe storage of objects within one or more federated areas, the one ormore federated devices may provide a portal accessible to other devicesvia a network for use in storing and retrieving objects associated withthe performances of analyses by other devices. More specifically, one ormore source devices may access the portal through the network to providethe one or more federated devices with the data objects, task routines,job flow definitions, DAGs and/or instance logs associated withcompleted performances of analyses by the one or more source devices forstorage within one or more federated areas for the purpose ofmemorializing the details of those performances. Subsequently, one ormore reviewing devices may access the portal through the network toretrieve such objects from one or more federated area through the one ormore federated devices for the purpose of independently confirmingaspects of such the performances.

As an alternative to or in addition to the provision of such a portal,the one or more federated devices may be caused to repeatedlysynchronize the contents of a selected federated area with an externalstorage space maintained by another device in a bidirectional manner,such as another source code repository system (e.g., GitHub™). Morespecifically, as object(s) within the external storage space of theother device are changed in any of a number of ways (e.g., added,edited, deleted, etc.), corresponding changes may be automatically madeto corresponding objects maintained within the federated area tosynchronize the contents therebetween. Similarly, as object(s) withinthe federated area are changed in any of a number of ways, correspondingchanges may be automatically made to corresponding objects maintainedwithin the external storage space of the other device, again, tosynchronize the contents therebetween.

Among the objects that may be stored in a federated area may be numerousdata objects that may include data sets. Each data set may be made up ofany of a variety of types of data concerning any of a wide variety ofsubjects. By way of example, a data set may include scientificobservation data concerning geological and/or meteorological events, orfrom sensors in laboratory experiments in areas such as particlephysics. By way of another example, a data set may include indicationsof activities performed by a random sample of individuals of apopulation of people in a selected country or municipality, or of apopulation of a threatened species under study in the wild. By way ofstill another example, a data set may include data descriptive of aneural network, such as hyperparameters that specify the quantity and/ororganization of nodes within the neural network, and/or such asparameters weights and biases of each of the nodes that may have beenderived through a training process in which the neural network istrained to perform a function.

Regardless of the types of data each such data set may contain, somedata sets stored in a federated area may include data sets employed asinputs to the performance of one or more job flows (e.g., flow inputdata sets), and/or other data sets stored in a federated area mayinclude data sets that are generated as outputs of past performance(s)of one or more job flows (e.g., result reports). It should be noted thatsome data sets that serve as inputs to the performance of one job flowmay be generated as an output of a past performance of another job flow(e.g., a result report becoming an flow input data set). Still otherdata sets may be both generated as an output and used as input during asingle performance of a job flow, such as a data set generated by theperformance of one task of a job flow for use by one or more other tasksof that same job flow (e.g., mid-flow data sets).

Also among the objects that may be stored in a federated area may be acombination of task routines and a job flow definition that, together,provide a combination of definitions and executable instructions thatenable the performance of an analysis as a job flow that is made up of aset of tasks to be performed. More precisely, executable instructionsfor the performance of an analysis may be required to be stored as a setof task routines where each task routine is made up of executableinstructions to perform a task, and a job flow definition that specifiesaspects of how the set of task routines are executed together to performthe analysis. In some embodiments, the definition of each task routinemay include definitions of the inputs and outputs thereof. In a job flowdefinition, each task to be performed may be assigned a flow taskidentifier, and each task routine that is to perform a particular taskmay be assigned the flow task identifier of that particular task to makeeach task routine retrievable by the flow task identifier of the task itperforms. Thus, each performance of an analysis may entail a parsing ofthe job flow definition for that analysis to retrieve the flow taskidentifiers of the tasks to be performed, and may then entail theretrieval of a task routine required to perform each of those tasks.

As will be explained greater detail, such breaking up of an analysisinto a job flow made up of tasks performed by the execution of taskroutines that are stored in federated area(s) may be relied upon toenable code reuse in which individual task routines may be shared amongthe job flows of multiple analyses. Such reuse of a task routineoriginally developed for one analysis by another analysis may be verysimply effected by specifying the flow task identifier of thecorresponding task in the job flow definition for the other analysis.Additionally, reuse may extend to the job flow definitions, themselves,as the availability of job flow definitions in a federated area mayobviate the need to develop of a new analysis routine where there is ajob flow definition already available that defines the tasks to beperformed in an analysis that may be deemed suitable. Thus, among theobjects that may be stored in a federated area may be numerousselectable and reusable task routines and job flow definitions.

In some embodiments, a job flow definition may be stored withinfederated area(s) as a file or other type of data structure in which thejob flow definition is represented as a DAG. Alternatively oradditionally, a file or other type of data structure may be used thatorganizes aspects of the job flow definition in a manner that enables aDAG to be directly derived therefrom. Such a file or data structure maydirectly indicate an order of performance of tasks, or may specifydependencies between inputs and outputs of each task to enable an orderof performance to be derived. By way of example, an array may be used inwhich there is an entry for each task routine that includesspecifications of its inputs, its outputs and/or dependencies on dataobjects that may be provided as one or more outputs of one or more othertask routines. Thus, a DAG may be usable to visually portray therelative order in which specified tasks are to be performed, while stillbeing interpretable by federated devices and/or other devices that maybe employed to perform the portrayed job flow. Such a form of a job flowdefinition may be deemed desirable to enable an efficient presentationof the job flow on a display of a reviewing device as a DAG. Thus,review of aspects of a performance of an analysis may be made easier bysuch a graphical representation of the analysis as a job flow.

The tasks that may be performed by any of the numerous tasks routinesmay include any of a variety of data analysis tasks, including and notlimited to searches for one or more particular data items, and/orstatistical analyses such as aggregation, identifying and quantifyingtrends, subsampling, calculating values that characterize at least asubset of the data items within a data object, deriving models, testinghypothesis with such derived models, making predictions, generatingsimulated samples, etc. The tasks that may be performed may also includeany of a variety of data transformation tasks, including and not limitedto, sorting operations, row and/or column-based mathematical operations,filtering of rows and/or columns based on the values of data itemswithin a specified row or column, and/or reordering of at least aspecified subset of data items within a data object into a specifiedascending, descending or other order. Alternatively or additionally, thetasks that may be performed by any of the numerous task routines mayinclude any of a variety of data normalization tasks, including and notlimited to, normalizing time values, date values, monetary values,character spacing, use of delimiter characters and/or codes, and/orother aspects of formatting employed in representing data items withinone or more data objects. The tasks performed may also include, and arenot limited to, normalizing use of big or little Endian encoding ofbinary values, use or lack of use of sign bits, the quantity of bits tobe employed in representations of integers and/or floating point values(e.g., bytes, words, doublewords or quadwords), etc. Also alternativelyor additionally, the tasks that may be performed may include tasks totrain one or more neural networks for use, tasks to test one or moretrained neural networks, tasks to coordinate a transition to the use ofa trained neural network to perform an analysis from the use of anon-neuromorphic approach to performing the analysis, and/or tasks tostore, retrieve and/or deploy a data set that specifies parametersand/or hyper parameters of a neural network.

The set of tasks that may be specified by the job flow definitions maybe any of a wide variety of combinations of analysis, normalizationand/or transformation tasks. The result reports generated throughperformances of the tasks as directed by each of the job flowdefinitions may include any of a wide variety of quantities and/or sizesof data. In some embodiments, one or more of the result reportsgenerated may contain one or more data sets that may be provided asinputs to the performances of still other analyses, and/or may beprovided to a reviewing device to be presented on a display thereof inany of a wide variety of types of visualization. In other embodiments,each of one or more of the result reports generated may primarilyinclude an indication of a prediction and/or conclusion reached throughthe performance of an analysis that generated the result report as anoutput.

Additionally among the objects that may be stored in a federated areamay be numerous instance logs that may each provide a record of variousdetails of a single past performance of a job flow. More specifically,each instance log may provide indications of when a performance of a jobflow occurred, along with identifiers of various objects stored withinfederated area(s) that were used and/or generated in that performance.Among those identifiers may be an identifier of the job flow definitionthat defines the job flow of an analysis that was performed, identifiersfor all of the task routines executed in that performance, identifiersfor any data objects employed as an input (e.g., input data sets), andidentifiers for any data objects generated as an output (e.g., a resultreport that may include one or more output data sets).

The one or more federated devices may assign such identifiers to dataobjects, task routines and/or job flow definitions as each is storedand/or generated within a federated area to enable such use ofidentifiers in the instance logs. In some embodiments, the identifierfor each such object may be generated by taking a hash of at least aportion of that object to generate a hash value to be used as theidentifier with at least a very high likelihood that the identifiergenerated for each such object is unique. Such use of a hash algorithmmay have the advantage of enabling the generation of identifiers forobjects that are highly likely to be unique with no other input than theobjects, themselves, and this may aid in ensuring that such anidentifier generated for an object by one federated device will beidentical to the identifier that would be generated for the same objectby another device.

Where task routines are concerned, it should be noted that the uniqueidentifier generated and assigned to each task routine is in addition tothe flow task identifier that identifies what task is performed by eachtask routine, and which are employed by the job flow definitions tospecify the tasks to be performed in a job flow. As will be explained ingreater detail, for each task identified in a job flow definition by aflow task identifier, there may be multiple task routines to choose fromto perform that task, and each of those task routines may be assigned adifferent identifier by the one or more federated devices to enable eachof those task routines to be uniquely identified in an instance log.Where instance logs are concerned, the identifier assigned to eachinstance log may, instead of being a hash taken of that instance log, bea concatenation or other form of combination of the identifiers of theobjects employed in the past performance that is documented by thatinstance log. In this way, and as will be explained in greater detail,the identifier assigned to each instance log may, itself, become usefulas a tool to locating a specific instance log that documents a specificpast performance.

The assignment of a unique identifier to each object (or at least anidentifier that is highly likely to be unique to each object) enableseach object to be subsequently retrieved from storage to satisfy arequest received by a federated device to access one or more specificobjects in which the request specifies the one or more specific objectsby their identifiers. Alternatively, requests may be received to provideaccess to multiple objects in which the multiple objects are specifiedmore indirectly. By way of example, a request may be received to provideaccess to a complete set of the objects that would be needed by therequesting device to perform a job flow with specified data set(s)serving as inputs, where it is the job flow definition and the dataset(s) that are directly identified in the request. Responding to such arequest may entail the retrieval of the specified job flow definitionand the specified data set(s) by the one or more federated devices,followed by the retrieval of the flow task identifiers for the tasks tobe performed from the job flow definition, followed by the use of theflow task identifiers to retrieve the most current version of taskroutine to perform each task, and then followed by the transmission ofthe specified job flow definition, the specified data set(s) and theretrieved task routines to the requesting device. By way of anotherexample, a request may be received to provide access to the objects thatare identified by an instance log as having been employed in a pastperformance of a job flow, where it is the instance log that is directlyidentified by its identifier in the request. Responding to such arequest may entail the retrieval of the specified instance log by one ormore federated devices, followed by the retrieval of the identifiers ofother objects from that instance log, and then followed by the retrievaland transmission of each of those other objects to the device from whichthe request was received. As will be explained in greater detail, stillother forms of indirect reference to objects stored within federatedarea(s) may be used in various requests.

In various embodiments, the one or more federated devices may receive arequest to provide one or more related objects together in a packagedform that incorporates one or more features that enable theestablishment of one or more new federated areas that contain therelated objects within the requesting device or within another device towhich the packaged form may be relayed. In some embodiments, thepackaged form may be that of a “zip” file in which the one or morerelated objects are compressed together into a single file that may alsoinclude executable code that enables the file to decompress itself, andin so doing, may also instantiate the one or more new federated areas.Such a packaged form may additionally include various executableroutines and/or data structures (e.g., indications of hash values, suchas checksum values, etc.) that enable the integrity of the one or morerelated objects to be confirmed, and/or that enable job flows based onthe one or more related objects to be performed. In generating thepackaged form, the one or more federated devices may employ variouscriteria specified in the request for which objects are to be providedin the packaged form to confirm that the objects so provided are acomplete enough set of objects as to enable any job flow that may bedefined by those objects to be properly performed.

In various embodiments, the use of federated area(s) may go beyond justthe storage and/or retrieval of objects, and may include the use ofthose stored objects by the one or more federated devices to perform jobflows. In such other embodiments, the one or more federated devices mayreceive requests (e.g., via the portal) from other devices to performvarious analyses that have been defined as job flows, and to provide anindication of the results to those other devices. More specifically, inresponse to such a request, the one or more federated devices mayexecute a combination of task routines to perform tasks of a job flowdescribed in a job flow definition within a federated area to therebyperform an analysis with one or more data objects, all of which arestored in one or more federated areas. In so doing, the one or morefederated devices may generate an instance log for storage within one ofthe one or more federated area that documents the performances of theanalysis, including identifiers of data objects used and/or generated,identifiers of task routines executed, and the identifier of the jobflow definition that specifies the task routines to be executed toperform the analysis as a job flow.

In some of such other embodiments, the one or more federated devices maybe nodes of a grid of federated devices across which the tasks of arequested performance of an analysis may be distributed. The provisionof a grid of the federated devices may make available considerableshared processing and/or storage resources to allow such a grid toitself perform complex analyses of large quantities of data, while stillallowing a detailed review of aspects of the performance of thatanalysis in situations where questions may arise concerning dataquality, correctness of assumptions made and/or coding errors. Duringthe performance of a job flow, the one or more federated devices mayanalyze the job flow definition for the job flow to identifyopportunities to perform multiple tasks in parallel based ondependencies among the tasks in which data generated as an output by onetask is needed as an input to another.

In some embodiments, the one or more federated devices may support theexecution of a set of task routines written in differing programminglanguages as part of performing a job flow. As will be explained ingreater detail, this may arise where it is deemed desirable to supportcollaborations among developers who are familiar with differingprogramming languages, but who are each contributing different objects,including task routines, the development of a job flow. To enable this,the one or more federated devices may employ a multitude of runtimeinterpreters and/or compilers for a pre-selected set of multipleprogramming languages to execute such a set of task routines during theperformance of a job flow.

As will also be explained in greater detail, during the performance of ajob flow, there may instances of a task routine generating a data set asan output that is to then be used as an input to one or more other taskroutines (e.g., a mid-flow data set). That data may be persisted bybeing stored in a federated area as a new data object that is assigned aunique identifier just as a data object received from a source devicewould be. As previously discussed, this may be done as part of enablingaccountability concerning how an analysis is performed by preservingdata sets that are generated as an output by one task routine for use asan input to another. However, where two or more task routines thatexchange a data set thereamong are written in different programminglanguages, the data set so exchanged may be subjected to a conversionprocess to in some way change its form (e.g., serialization orde-serialization) to accommodate differences in data types and/orformats that are supported by the different programming languages (e.g.,to resolve differences in the manner in which arrays are organizedand/or accessed). Where such a conversion is performed, it may be thatjust one of the forms of the data set may be persisted to a federatedarea while the other form may be temporarily stored in a shared memoryspace that may be instantiated just for the duration of the performanceof the job flow and that may be un-instantiated at the end of thatperformance.

Some requests to perform a job flow may include a request to perform aspecified job flow of an analysis with one or more specified dataobjects. Other requests may be to repeat a past performance of a jobflow that begat a specified result report, or that entailed the use of aspecific combination of a job flow and one or more data sets as inputs.Through the generation of identifiers for each of the various objectsassociated with each performance of a job flow, through the use of thoseidentifiers to refer to such objects in instance logs, and through theuse of those identifiers by the one or more federated devices inaccessing such objects, requests for performances of analyses are ableto more efficiently identify particular performances, their associatedobjects and/or related objects.

In embodiments in which a request is received to perform a specified jobflow of an analysis with one or more specified data objects as inputs,the one or more federated devices may use the identifiers of thoseobjects that are provided in the request to analyze the instance logsstored in one or more federated areas to determine whether there was apast performance of the same job flow with the same one or more dataobjects as inputs. If there was such a past performance, then the resultreport generated as the output of that past performance may already bestored in a federated area. As long as none of the task routinesexecuted in the earlier performance have been updated since the earlierperformance, then a repeat performance of the same job flow with thesame one or more data objects serving as inputs may not be necessary.Thus, if any instance logs are found for such an earlier performance,the one or more federated devices may analyze the instance logassociated with the most recent earlier performance (if there has beenmore than one past performance) to obtain the identifiers uniquelyassigned to each of the task routines that were executed in that earlierperformance. The one or more federated devices may then analyze each ofthe uniquely identified task routines to determine whether each of themcontinues to be the most current version stored in the federated areafor use in performing its corresponding task. If so, then a repeatedperformance of the job flow with the one or more data objects identifiedin the request is not necessary, and the one or more federated devicesmay retrieve the result report generated by the past performance from afederated area and transmit that result report to the device from whichthe request was received.

However, if no instance logs are found for any past performance of thespecified job flow with the specified one or more data objects thatentailed the execution of the most current version of each of the taskroutines, then the one or more federated devices may perform thespecified job flow with the specified data objects using the mostcurrent version of task routine for each task specified with a flow taskidentifier in the job flow definition. Indeed, and as will be explainedin greater detail, it may be that the most current version of each taskroutine may be selected and used in performing a task by default, unlessa particular earlier version is actually specified to be used. The oneor more federated devices may then assign a unique identifier to andstore the new result report generated during such a performance in afederated area, as well as transmit the new result report to the devicefrom which the request was received. The one or more federated devicesmay also generate and store in a federated area a corresponding newinstance log that specifies details of the performance, including theidentifier of the job flow definition, the identifiers of all of themost current versions of task routines that were executed, theidentifiers of the one or more data objects used as inputs and/orgenerated as outputs, and the identifier of the new result report thatwas generated.

In embodiments in which a request is received to repeat a pastperformance of a job flow of an analysis that begat a result reportidentified in the request by its uniquely assigned identifier, the oneor more federated devices may analyze the instance logs stored in one ormore federated areas to retrieve the instance log associated with thepast performance that resulted in the generation of the identifiedresult report. The one or more federated devices may then analyze theretrieved instance log to obtain the identifiers for the job flowdefinition that defines the job flow, the identifiers for each of thetask routines executed in the past performance, and the identifiers ofany data objects used as inputs in the past performance. Upon retrievingthe identified job flow definition, each of the identified taskroutines, and any identified data objects, the one or more federateddevices may then execute the retrieved task routines, using theretrieved data objects, and in the manner defined by the retrieved jobflow definition to repeat the past performance of the job flow withthose objects to generate a new result report. Since the request was torepeat an earlier performance of the job flow with the very sameobjects, the new result report should be identical to the earlier resultreport generated in the past performance such that the new result reportshould be a regeneration of the earlier result report. The one or morefederated devices may then assign an identifier to and store the newresult report in a federated area, as well as transmit the new resultreport to the device from which the request was received. The one ormore federated devices may also generate and store, in a federated area,a corresponding new instance log that specifies details of the newperformance of the job flow, including the identifier of the job flowdefinition, the identifiers of all of the task routines that wereexecuted, the identifiers of the one or more data objects used as inputsand/or generated as outputs, and the identifier of the new resultreport.

In some embodiments, a request for a performance of a job flow (whetherit is a request to repeat a past performance, or not) may specify thatthe input/output behavior of the task routines used during theperformance be verified. More specifically, it may be requested that theinput/output behavior of the task routines that are executed during theperformance of a job flow be monitored, and that the observedinput/output behavior of each of those task routines with regard toaccessing data objects and/or engaging in any other exchange of inputsand/or outputs be compared to the input and/or output interfaces thatmay be implemented by their executable instructions, that may bespecified in any comments therein, and/or that may be specified in thejob flow definition of the job flow that is performed. Each task routinethat exhibits input/output behavior that remains compliant with suchspecifications during its execution may be in some way marked and/orrecorded as having verified input/output behavior. Each task routinethat exhibits input/output behavior that goes beyond such specificationsmay be in some way marked and/or recorded as having aberrantinput/output behavior.

To perform such monitoring of the input/output behavior of taskroutines, each task routine that is executed during the performance of aparticular job flow may be so executed within a container environmentinstantiated within available storage space by a processor of one of thefederated devices. More specifically, such a container environment maybe defined to limit accesses that may be made to other storage spacesoutside the container environment and/or to input and/or output devicesof the federated device. In effect, such a container environment may begiven a set of access rules by which input/output behaviors that complywith input/output behaviors that are expected of particular task routineare allowed to proceed, while other input/output behaviors that gobeyond the expected input/output behaviors may be blocked while thestorage locations that were meant to be accessed by those aberrantinput/output behaviors are recorded to enable accountability for suchmisbehavior by a task routine, and/or to serve as information that maybe required by a programmer to correct a portion of the executableinstructions within such a task routine to correct its input/outputbehavior.

By way of example, and still more specifically, such comments within atask routine and/or such specifications within a job flow definition mayspecify various aspects of its inputs and/or outputs, such data type,indexing scheme, etc. of data object(s), but may refrain from specifyingany particular data object as part of an approach to allowing particulardata object(s) to be specified by a job flow definition, or in any of avariety of other ways, during the performance of the job flow in whichthe task routine may be executed and/or that is defined by the job flowdefinition. Instead, a placeholder designator (e.g., a variable) may bespecified that is to be given a value indicative of a specific dataobject during the performance of a job flow. Alternatively, where one ormore particular data objects are specified, such specification of one ormore particular data objects may be done as a default to address asituation in which one or more particular data objects are not specifiedby a job flow definition and/or in another way during performance of ajob flow in which the task routine may be executed. Regardless ofwhether particular data objects are specified, following the retrievaland interpretation of such input/output specifications, a containerenvironment may be instantiated that is configured to enable the taskroutine to be executed therein and that allows the task routine toengage in input/output behavior that conforms to those input/outputspecifications, but which does not allow the task routine to engage inaberrant input/output behavior that goes beyond what it is expectedbased on those input/output specifications. Depending on theinput/output behavior that is observed as the task routine is soexecuted, the task routine may be marked as being verified as engagingin correct input/output behavior or may be marked as being observedengaging in aberrant input/output behavior.

In some embodiments, the marking of the results of such monitoring ofinput/output behavior of each task routine may be incorporated into taskroutine database(s) that may be used to organize the storage of taskroutines within one or more federated areas as part of enabling moreefficient selection and retrieval of task routines for provision to arequesting device and/or for execution. In some of such embodiments,such marking of task routines may also play a role in which taskroutines are selected to be provided to a requesting device and/or to beexecuted as part of performing a job flow. As an alternative to suchmarking of such input/output behavior of a task routine being maintainedby a task routine database, a separate and distinct data structure maybe maintained within the federated area in which the task routine isstored as a repository of indications of such input/output behavior bythe task routine and/or by multiple task routines (e.g., a data file ofsuch indications). Alternatively or additionally, and regardless of theexact manner in which such indications of such input/output behavior ofa task routine may be stored, in some embodiments, such storedindications of either correct or aberrant input/output behavior of atask routine may be reflected in instance logs from performances of jobflows in which the task routine was executed and/or in a visualrepresentation of the task routine in a DAG.

In various embodiments, a job flow definition may be augmented withgraphical user interface (GUI) instructions that are to be executedduring a performance of the job flow that it defines to provide a GUIthat provides a user an opportunity to specify one or more aspects ofthe performance of the job flow at runtime. By way of example, such aGUI may provide a user with an opportunity to select one or more dataobjects to be used as inputs to that performance, to select which one ofmultiple versions of a task routine is to be used to perform a task,and/or select a federated area into which to store a result report to beoutput by that performance. In so doing, the GUI may includeinstructions to display lists of objects, characteristics of objects,DAGs of objects, etc. in response to specific inputs received from auser.

In some of such embodiments, the source device that provides such anaugmented job flow definition to the one or more federated devices forstorage may enable a user to author such GUI instructions through use ofa sketch input user interface. More specifically, such a source devicemay support the entry of GUI instructions as graphical symbols sketchedby a user of the source device through a touchscreen user interfacedevice that supports sketch input and a stylus. Such a source device maymaintain a library of graphical symbols that are each correlated to aparticular type of object, to a particular characteristic of an objectand/or to the displaying of particular information in connection to aparticular type of object. Alternatively or additionally, such a librarymay include graphical symbols that are correlated to particular types ofuser input that is to be awaited and/or to particular types of actionsto be taken in response to the receipt of particular types of userinput. One or more of such graphical symbols may include human readabletext that may be employed to specify distinct pages of a GUI and/or tospecify particular objects. Such a source device may interpret thegraphical symbols, any text incorporated therein, and/or the manner inwhich those graphical symbols are arranged relative to each other in thesketch input to derive and generate the GUI instructions with which ajob flow definition is to be augmented.

In support enabling the objects stored within one or more federatedareas to be used in performances of job flows, and/or in support ofenabling accountability in analyzing aspects of a past performance of ajob flow, a set of rules may be enforced by the one or more federateddevices that limit what actions may be taken in connection with eachobject. Such enforced limitations in access to each object may be inaddition to the aforementioned restrictions on accesses to federatedarea(s) that may be imposed on entities, persons and/or particulardevices. Such rules may restrict what objects are permitted to be storedand/or when, and/or may restrict what objects are able to be alteredand/or removed as part of preventing instances of there being “orphan”objects that are not accompanied in storage by other objects that may beneeded to support a performance or a repetition of a performance of ajob flow. Alternatively or additionally, such rules may restrict whatobjects are permitted to be stored and/or when as part of preventinstances of incompatibility between objects that are to be usedtogether in a performance of a job flow.

By way of example, whether a job flow definition will be permitted to bestored within a federated area may be made contingent on whether, foreach task that is specified in the job flow definition, there is atleast one task routine that is already stored in the federated areaand/or is about to be stored in the federated area along with the jobflow definition. Such a rule that imposes such a condition on thestorage of a job flow definition may be deemed desirable to prevent asituation in which there is a job flow definition stored in a federatedarea that defines a job flow that cannot be performed as a result ofthere being a task specified therein that cannot be performed due to thelack of storage in a federated area of any task routine that can beexecuted to perform that task. Similarly, and by way of another example,whether an instance log will be permitted to be stored within afederated area may be made contingent on whether each object identifiedin the instance log as being associated with a past performance of thejob flow documented by the instance log is already stored in thefederated area and/or is about to be stored in the federated area alongwith the instance log. Such a rule that imposes such a condition on thestorage of an instance log may be deemed desirable to prevent asituation in which there is an instance log stored in a federated areathat documents a past performance of a job flow that cannot be repeateddue to the lack of storage in a federated area of an object specified inthe instance log as being associated with that past performance.

By way of another example, whether a job flow definition will bepermitted to be stored within a federated area may alternatively oradditionally be made contingent on whether, the input and/or outputinterfaces specified for each task in the job flow definition are asufficient match to the input and/or output definitions implemented bythe already stored task routines that perform each of those tasks. Sucha rule that imposes such a condition on the storage of a job flowdefinition may be deemed desirable to prevent incompatibilities betweenthe specifications of interfaces in a job flow definition and theimplementations of interfaces in the corresponding task routines.Similarly, and by way of still another example, whether a new version ofa task routine that performs a particular task when executed will bepermitted to be stored within a federated area may be made contingent onwhether, the input and/or output definitions implemented within the newtask routine are a sufficient match to the input and/or outputdefinitions implemented by the one or more already stored task routinesthat also perform the same task. Such a rule that imposes such acondition on the storage of a new task routine may be deemed desirableto prevent incompatibilities between versions of task routines thatperform the same task.

By way of still another example, whether a data object (e.g., flow inputdata set, a mid-flow data set, or result report) or a task routine ispermitted to be deleted from a federated area may be made contingent onwhether its removal would prevent a job flow that is defined in a jobflow definition from being performed and/or whether its removal wouldprevent a past performance of a job flow that is documented by ainstance log from being repeated. Such a rule that imposes such acondition may be deemed desirable to prevent a situation in which thereis a job flow definition stored in a federated area that defines a jobflow that cannot be performed due to the lack of storage in a federatedarea of any task routine that can be executed to perform one of thetasks specified in the job flow definition. Also, such a rule thatimposes such a condition may be deemed desirable to prevent a situationin which there is an instance log stored in a federated area thatdocuments a past performance of a job flow that cannot be repeated dueto the lack of storage in a federated area of a data object or taskroutine specified in the instance log as being associated with that pastperformance. Similarly, and by way of yet another example, whether a jobflow definition is permitted to be deleted from a federated area may bemade contingent on whether its removal would prevent a past performanceof the corresponding job flow that is documented by a instance log frombeing repeated. Such a rule that imposes such a condition may be deemeddesirable to prevent a situation in which there is an instance logstored in a federated area that documents a past performance of a jobflow that cannot be repeated due to the lack of storage in a federatedarea of the job flow definition for that job flow.

With such restrictions against the removal of objects from a federatedarea, an alternative that may be allowed by the set of rules may be thestoring of newer versions of objects. By way of example, where anearlier version of a task routine or a job flow definition is determinedto have flaws and/or to be in need of replacement for some other reason,the set of rules may allow a newer (and presumably improved) version ofsuch a task routine or job flow definition to be stored so that it canbe used instead of the earlier version. As previously discussed, whileeach version of each task routine may be assigned a unique identifiergenerated from the taking of a hash of thereof such that each version ofeach task routine is individually identifiable and selectable, each taskroutine is also assigned a flow task identifier that specifies the taskthat it performs when executed. As previously discussed, task routinesmay subsequently be searched for and selected based on their flow taskidentifiers, and use of the most current version of task routine toperform each task specified in a job flow by a flow task identifier maybe the default rule. As a result, the storage of a new version of a taskroutine that performs a task identified by a particular flow taskidentifier may be relied upon to cause the use of any earlier versionsof task routine that also perform that same task identified by that sameflow task identifier to cease, except in situations where the use of aparticular earlier version of task routine to perform a particular taskis actually specified.

Through such pooling of older and newer versions of objects, through theprovision of unique identifiers for each object, and through theenforcement of such a regime of rules restricting accesses that may bemade to one or more federated areas, objects such as data sets, taskroutines and job flow definitions are made readily available for reuseunder conditions in which their ongoing integrity against inadvertentand/or deliberate alteration is assured. The provision of a flow taskidentifier for each task may enable updated versions of task routines tobe independently created and stored within one or more federated areasin a manner that associates those updated versions with earlier versionswithout concern of accidental overwriting of earlier versions.

As a result of such pooling of data sets and task routines, new analysesmay be more speedily created through reuse thereof by generating new jobflows that identify already stored data sets and/or task routines.Additionally, where a task routine is subsequently updated, advantagemay be automatically taken of that updated version in subsequentperformances of each job flow that previously used the earlier versionof that task routine. And yet, the earlier version of that task routineremains available to enable a comparative analysis of the resultsgenerated by the different versions if discrepancies therebetween aresubsequently discovered. Also, as a result of such pooling of data sets,task routines and job flows, along with instance logs and resultreports, repeated performances of a particular job flow with aparticular data set can be avoided. Through use of identifiers uniquelyassociated with each object and recorded within each instance log,situations in which a requested performance of a particular job flowwith a particular data set that has been previously performed can bemore efficiently identified, and the result report generated by thatprevious performance can be more efficiently retrieved and madeavailable in lieu of consuming time and processing resources to repeatthat previous performance. And yet, if a question should arise as to thevalidity of the results of that previous performance, the data set(s),task routines and job flow definition on which that previous performancewas based remain readily accessible for additional analysis to resolvethat question.

Also, where there is no previous performance of a particular job flowwith a particular data set such that there is no previously generatedresult report and/or instance log therefor, the processing resources ofthe grid of federated devices may be utilized to perform the particularjob flow with the particular data set. The ready availability of theparticular data set to the grid of federated devices enables such aperformance without the consumption of time and network bandwidthresources that would be required to transmit the particular data set andother objects to the requesting device to enable a performance by therequesting device. Instead, the transmissions to the requesting devicemay be limited to the result report generated by the performance. Also,advantage may be taken of the grid of federated devices to cause theperformance of one or more of the tasks of the job flow as multipleinstances thereof in a distributed manner (e.g., at least partially inparallel) among multiple federated devices and/or among multiple threadsof execution support by processor(s) within each such federated device.

As a result of the requirement that the data set(s), task routines andthe job flow associated with each instance log be preserved,accountability for the validity of results of past performances of jobflows with particular data sets is maintained. The sources of incorrectresults, whether from invalid data, or from errors made in the creationof a task routine or a job flow, may be traced and identified. By way ofexample, an earlier performance of a particular job flow with aparticular data set using earlier versions of task routines can becompared to a later performance of the same job flow with the same dataset, but using newer versions of the same task routines, as part of ananalysis to identify a possible error in a task routine. As a result,mistakes can be corrected and/or instances of malfeasance can beidentified and addressed.

The one or more federated devices may maintain one or more sets offederated areas that may be related to each other through a set ofrelationships that serve to define a hierarchy of federated areas inwhich the different federated areas may be differentiated by the degreeof restriction of access thereto that may be enforced by the one or morefederated devices. In some embodiments, a linear hierarchy may bedefined in which there is a base federated area with the leastrestricted degree of access, a private federated area with the mostrestricted degree of access, and/or one or more intervening federatedareas with intermediate degrees of access restriction interposed betweenthe base and private federated areas. Such a hierarchy of federatedareas may be created to address any of a variety of situations insupport of any of a variety of activities, including those in whichdifferent objects stored thereamong require different degrees of accessrestriction. By way of example, while a new data set or a new taskroutine is being developed, it may be deemed desirable to maintain itwithin the private federated area or intervening federated area to whichaccess is granted to a relatively small number of users (e.g., personsand/or other entities that may each be associated with one or moresource devices and/or reviewing devices) that are directly involved inthe development effort. It may be deemed undesirable to have such a newdata set or task routine made accessible to others beyond the usersinvolved in such development before such development is completed, suchthat various forms of testing and/or quality assurance have beenperformed. Upon completion of such a new data set or task routine, itmay then be deemed desirable to transfer it, or a copy thereof, to thebase federated area or other intervening federated area to which accessis granted to a larger number of users. Such a larger number of usersmay be the intended users of such a new data set or task routine.

It may be that multiple ones of such linear hierarchical sets offederated areas may be combined to form a tree of federated areas with asingle base federated area with the least restricted degree of access atthe root of the tree, and multiple private federated areas as the leavesof the tree that each have more restricted degrees of access. Such atree may additionally include one or more intervening federated areaswith various intermediate degrees of access restriction to define atleast some of the branching of hierarchies of federated areas within thetree. Such a tree of federated areas may be created to address any of avariety of situations in support of any of a variety of larger and/ormore complex activities, including those in which different users thateach require access to different objects at different times are engagedin some form of collaboration. By way of example, multiple users may beinvolved in the development of a new task routine, and each such usermay have a different role to play in such a development effort. Whilethe new task routine is still being architected and/or generated, it maybe deemed desirable to maintain it within a first private federated areaor intervening federated area to which access is granted to a relativelysmall number of users that are directly involved in that effort. Uponcompletion of such an architecting and/or generation process, the newtask routine, or a copy thereof, may be transferred to a second privatefederated area or intervening federated area to which access is grantedto a different relatively small number of users that may be involved inperforming tests and/or other quality analysis procedures on the newtask routine to evaluate its fitness for release for use. Uponcompletion of such testing and/or quality analysis, the new taskroutine, or a copy thereof, may be transferred to a third privatefederated area or intervening federated area to which access is grantedto yet another relatively small number of users that may be involved inpre-release experimental use of the new task routine to further verifyits functionality in actual use case scenarios. Upon completion of suchexperimental use, the new task routine, or a copy thereof, may betransferred to a base federated area or other intervening federated areato which access is granted to a larger number of users that may be theintended users of the new task routine.

In embodiments in which multiple federated areas form a tree offederated areas, each user may be automatically granted their ownprivate federated area as part of being granted access to at least aportion of the tree. Such an automated provision of a private federatedarea may improve the ease of use, for each such user, of at least thebase federated area by providing a private storage area in which aprivate set of job flow definitions, task routines, data sets and/orother objects may be maintained to assist that user in the developmentand/or analysis of other objects that may be stored in at least the basefederated area. By way of example, a developer of task routines maymaintain a private set of job flow definitions, task routines and/ordata sets in their private federated area for use as tools indeveloping, characterizing and/or testing the task routines that theydevelop. The one or more federated devices may be caused, by such adeveloper, to use such job flow definitions, task routines and/or datasets to perform compilations, characterizing and/or testing of such newtask routines within the private federated area as part of thedevelopment process therefor. Some of such private job flow definitions,task routines and/or data sets may include and/or may be importantpieces of intellectual property that such a developer desires to keep tothemselves for their own exclusive use (e.g., treated as trade secretsand/or other forms of confidential information).

A base federated area within a linear hierarchy or hierarchical tree offederated areas may be the one federated area therein with the leastrestrictive degree of access such that a grant of access to the basefederated area constitutes the lowest available level of access that canbe granted to any user. Stated differently, the base federated area mayserve as the most “open” or most “public” space within a linearhierarchy or hierarchical tree of federated spaces. Thus, the basefederated area may serve as the storage space at which may be stored jobflow definitions, versions of task routines, data sets, result reportsand/or instance logs that are meant to be available to all users thathave been granted any degree of access to the set of federated areas ofwhich the base federated area is a part. The one or more federateddevices may be caused, by a user that has been granted access to atleast the base federated area, to perform a job flow within the basefederated area using a job flow definition, task routines and/or datasets stored within the base federated area.

In a linear hierarchical set of federated areas that includes a basefederated area and just a single private federated area, one or moreintervening federated areas may be interposed therebetween to supportthe provision of different levels of access to other users that don'thave access to the private federated area, but are meant to be givenaccess to more than what is stored in the base federated area. Such aprovision of differing levels of access would entail providing differentusers with access to either just the base federated area, or to one ormore intervening federated areas. Of course, this presumes that eachuser having any degree of access to the set of federated areas is notautomatically provided with their own private federated area, as theresulting set of federated areas would then define a tree that includesmultiple private federated areas, and not a linear hierarchy thatincludes just a single private federated area.

In a hierarchical tree of federated areas that includes a base federatedarea at the root and multiple private federated areas at the leaves ofthe tree, one or more intervening federated areas may be interposedbetween one or more of the private federated areas and the basefederated areas in a manner that defines at least part of one or morebranches of the tree. Through such branching, different privatefederated areas and/or different sets of private federated areas may belinked to the base federated area through different interveningfederated areas and/or different sets of intervening federated areas. Inthis way, users associated with some private federated areas within onebranch may be provided with access to one or more intervening federatedareas within that branch that allow sharing of objects thereamong, whilealso excluding other users associated with other private federated areasthat may be within one or more other branches. Stated differently,branching may be used to create separate sets of private federated areaswhere each such set of private federated areas is associated with agroup of users that have agreed to more closely share objectsthereamong, while all users within all of such groups are able to shareobjects through the base federated area, if they so choose.

In embodiments in which there are multiple federated areas that formeither a single linear hierarchy or a hierarchical tree, each of thefederated areas may be assigned one or more identifiers. It may be thateach federated area is assigned a human-readable identifier, such asnames that are descriptive of ownership (e.g., “Frank's”), names thatare descriptive of degree of access (e.g., “public” vs. “private”),names of file system directories and/or sub-directories at which each ofthe federated areas may be located, and/or names of network identifiersby which each federated area may be accessible on a network. However, itmay be that each federated area is also assigned a randomly generatedidentifier with a large enough bit width that it is highly likely thateach such identifier is unique across all federated areas anywhere inthe world (e.g., a “global” identifier or “GUID”). Such a uniqueidentifier for each federated area may provide a mechanism to resolveidentification conflicts where perhaps two or more federated areas mayhave been given identical human-readable identifiers.

In one example of assignment and use of identifiers, a set of federatedareas that form either a single linear hierarchy or hierarchical treemay be assigned identifiers that make the linear hierarchy orhierarchical tree navigable through the use of typical web browsingsoftware. More specifically, one or more federated devices may generatethe portal to enable access, by a remote device, to the set of federatedareas from across a network using web access protocols, file transferprotocols and/or other protocols in which each of multiple federatedareas is provided with a human-readable identifier in the form of auniform resource locator (URL). In so doing, the URLs assigned theretomay be structured to reflect the hierarchy that has been defined amongthe federated areas therein. Thus, for a tree of federated areas, thebase federated area at the root of the tree may be assigned the shortestand simplest URL, and such a URL given to the base federated area may beindicative of a name given to that entire tree of federated areas. Incontrast, the URL of each federated area at a leaf of the tree mayinclude a combination (e.g., a concatenation) of at least a portion ofthe URL given to the base federated area, and at least a portion of theURL given to any intervening federated area in the path between thefederated area at the leaf and the base federated area.

In embodiments of either a linear hierarchy of federated areas or ahierarchical tree of federated areas, one or more relationships thataffect the manner in which objects may be accessed and/or used may beput in place between each private federated area and the base federatedarea, as well as through any intervening federated areas therebetween.Among such relationships may be an inheritance relationship in which,from the perspective of a private federate area, objects stored withinthe base federated area, or within any intervening federated areatherebetween, may be treated as if they are also stored directly withinthe private federated area for purposes of being available for use inperforming a job flow within the private federated area. As will beexplained in greater detail, the provision of such an inheritancerelationship may aid in enabling and/or encouraging the reuse of objectsby multiple users by eliminating the need to distribute multiple copiesof an object among multiple private federated areas in which that objectmay be needed for performances of job flows within each of those privatefederated areas. Instead, a single copy of such an object may be storedwithin the base federated area and will be treated as being just asreadily available for use in performances of job flows within each ofsuch private federated areas.

Also among such relationships may be a priority relationship in which,from the perspective of a private federated area, the use of a versionof an object stored within the private federated area may be givenpriority over the use of another version of the same object storedwithin the base federated area, or within any intervening federated areatherebetween. More specifically, where a job flow is to be performedwithin a private federated area, and there is one version of a taskroutine to perform a task of the job flow stored within the privatefederated area and another version of the task routine to perform thesame task stored within the base federated area, use of the version ofthe task routine stored within the private federated area may be givenpriority over use of the other version stored within the base federatedarea. Further, such priority may be given to using the version storedwithin the private federated area regardless of whether the otherversion stored in the base federated area is a newer version. Stateddifferently, as part of performing the job flow within the privatefederated area, the one or more federated devices may first searchwithin the private federated area for any needed task routines toperform each of the tasks specified in the job flow, and upon finding atask routine to perform a task within the private federated area, nosearch may be performed of any other federated area to find a taskroutine to perform that same task. It may be deemed desirable toimplement such a priority relationship as a mechanism to allow a userassociated with the private federated area to choose to override theautomatic use of a version of a task routine within the base federatedarea (or an intervening federated area therebetween) due to aninheritance relationship by storing the version of the task routine thatthey prefer to use within the private federated area.

Also among such relationships may be a dependency relationship in which,from the perspective of a private federated area, some objects storedwithin the private federated area may have dependencies on objectsstored within the base federated area, or within an interveningfederated area therebetween. More specifically, as earlier discussed,the one or more federated devices may impose a rule that the taskroutines upon which a job flow depends may not be deleted such that theone or more federated devices may deny a request received from a remotedevice to delete a task routine that performs a task identified by aflow task identifier that is referred to by at least one job flowdefinition stored. Thus, where the private federated area stores a jobflow definition that includes a flow task identifier specifying aparticular task to be done, and the base federated area stores a taskroutine that performs that particular task, the job flow of the job flowdefinition may have a dependency on that task routine continuing to beavailable for use in performing the task through an inheritancerelationship between the private federated area and the base federatedarea. In such a situation, the one or more federated devices may deny arequest that may be received from a remote device to delete that taskroutine from the base federated area, at least as long as the job flowdefinition continues to be stored within the private federated area.However, if that job flow definition is deleted from the privatefederated area, and if there is no other job flow definition that refersto the same task flow identifier, then the one or more federated devicesmay permit the deletion of that task routine from the base federatedarea.

In embodiments in which there is a hierarchical tree of federated areasthat includes at least two branches, a relationship may be put in placebetween two private and/or intervening federated areas that are eachwithin a different one of the two branches by which one or more objectsmay be automatically transferred therebetween by the one or morefederated devices in response to one or more conditions being met. Aspreviously discussed, the formation of branches within a tree may beindicative of the separation of groups of users where there may besharing of objects among users within each such group, such as throughthe use of one or more intervening federated areas within a branch ofthe tree, but not sharing of objects between such groups. However, theremay be occasions in which there is a need to enable a relatively limiteddegree of sharing of objects between federated areas within differentbranches. Such an occasion may be an instance of multiple groups ofusers choosing to collaborate on the development of one or moreparticular objects such that those particular one or more objects are tobe shared among the multiple groups where, otherwise, objects would notnormally be shared therebetween. On such an occasion, the one or morefederated devices may be requested to instantiate a transfer areathrough which those particular one or more objects may be automaticallytransferred therebetween upon one or more specified conditions beingmet. In some embodiments, the transfer area may be formed as an overlapbetween two federated areas of two different branches of a hierarchicaltree. In other embodiments, the transfer area may be formed within thebase federated area to which users associated with federated areaswithin different branches may all have access.

In some embodiments, the determination of whether the condition(s) for atransfer have been met and/or the performance of the transfer of one ormore particular objects may be performed using one or more transferroutines to perform transfer-related tasks called for within a transferflow definition. In such embodiments, a transfer routine may be storedwithin each of the two federated areas between which the transfer is tooccur. Within the federated area that the particular one or more objectsare to be transferred from, the one or more federated devices may becaused by the transfer routine stored therein to repeatedly checkwhether the specified condition(s) have been met, and if so, to thentransfer copies of the particular one or more objects into the transferarea. Within the federated area that the particular one or more objectsare to be transferred to, the one or more federated devices may becaused by the transfer routine stored therein to repeatedly checkwhether copies of the particular one or more objects have beentransferred into the transfer area, and if so, to then retrieve thecopies of the particular one or more objects from the transfer area.

A condition that triggers such automated transfers may be any of avariety of conditions that may eventually be met through one or moreperformances of a job flow within the federated area from which one ormore objects are to be so transferred. More specifically, the conditionmay be the successful generation of particular results data that mayinclude a data set that meets one or more requirements that arespecified as the condition. Alternatively, the condition may be thesuccessful generation and/or testing of a new task routine such thatthere is confirmation in a result report or in the generation of one ormore particular data sets that the new task routine has beensuccessfully verified as meeting one or more requirements that arespecified as the condition. As will be explained in greater detail, theone or more performances of a job flow that may produce an output thatcauses the condition to be met may occur within one or more processesthat may be separate from the process in which a transfer routine isexecuted to repeatedly check whether the condition has been met. Also,each of such processes may be performed on a different thread ofexecution of a processor of a federated device, or each of suchprocesses may be performed on a different thread of execution of adifferent processor from among multiple processors of either a singlefederated device or multiple federated devices.

By way of example, multiple users may be involved in the development ofa new neural network, and each such user may have a different role toplay in such a development effort. While the new neural network is beingdeveloped through a training process, it may be deemed desirable tomaintain the data set of weights and biases that is being generatedthrough numerous iterations of training within a first interveningfederated area to which access is granted to a relatively small numberof users that are directly involved in that training effort. Uponcompletion of such training of the neural network, a copy of the dataset of weights and biases may be transferred to a second interveningfederated area to which access is granted to a different relativelysmall number of users that may be involved in testing the neural networkdefined by the data set to evaluate its fitness for release for use. Thetransfer of the copy of the data set from the first interveningfederated area to the second intervening federated area may be triggeredby the training having reached a stage at which a predeterminedcondition is met that defines the completion of training, such as aquantity of iterations of training having been performed. Uponcompletion of such testing of the neural network, a copy of the data setof weights and biases may be transferred from the second interveningfederated area to a third intervening federated area to which access isgranted to yet another relatively small number of users that may beinvolved in pre-release experimental use of the neural network tofurther verify its functionality in actual use case scenarios. Like thetransfer to the second intervening federated area, the transfer of thecopy of the data set from the second intervening federated area to thethird intervening federated area may be triggered by the testing havingreached a stage at which a predetermined condition was met that definesthe completion of testing, such as a threshold of a characteristic ofperformance of the neural network having been found to have been metduring testing. Upon completion of such experimental use, a copy of thedata set of weights and biases may be transferred from the thirdfederated area to a base federated area to which access is granted to alarger number of users that may be the intended users of the new neuralnetwork.

Such a neural network may be generated as part of an effort totransition from performing a particular analytical function usingnon-neuromorphic processing (i.e., processing in which a neural networkis not used) to performing the same analytical function usingneuromorphic processing (i.e., processing in which a neural network isused). Such a transition may represent a tradeoff in accuracy for speed,as the performance of the analytical function using neuromorphicprocessing may not achieve the perfect accuracy (or at least the degreeof accuracy) that is possible via the performance of the analyticalfunction using non-neuromorphic processing, but the performance of theanalytical function using neuromorphic processing may be faster by oneor more orders of magnitude, depending on whether the neural network isimplemented with software-based simulations of its artificial neuronsexecuted by one or more CPUs or GPUs, or hardware-based implementationsof its artificial neurons provided by one or more neuromorphic devices.

Where the testing of such a neural network progresses successfully suchthat the neural network begins to be put to actual use, there may be agradual transition from the testing to the usage that may beautomatically implemented in a staged manner Initially, non-neuromorphicand neuromorphic implementations of the analytical function may beperformed at least partially in parallel with the same input data valuesbeing provided to both, and with the corresponding output data values ofeach being compared to test the degree of accuracy of the neural networkin performing the analytical function. In such initial, at leastpartially parallel, performances, priority may be given to providingprocessing resources to the non-neuromorphic implementation, since thenon-neuromorphic implementation is still the one that is in use. As theneural network demonstrates a degree of accuracy that at least meets apredetermined threshold, the testing may change such that theneuromorphic implementation is used, and priority is given to providingprocessing resources to it, while the non-neuromorphic implementation isused at least partially in parallel solely to provide output data valuesfor further comparisons to corresponding ones provided by theneuromorphic implementation. Presuming that the neural network continuesto demonstrate a degree of accuracy that meets or exceeds thepredetermined threshold, further use of the non-neuromorphicimplementation of the analytical function may cease, entirely.

In various embodiments, a somewhat similar temporary relationship may beinstantiated between a selected federated area and a storage space thatis entirely external to the one or more federated devices and/or to theone or more federated areas, such as an external storage spacemaintained by a source device or a reviewing device. The federated areaselected for such a relationship may, again, be a private federated areaor other federated area (e.g., an intermediate federated area) used tostore one or more objects that may be under development. The purpose ofsuch a relationship may be to cause the automatic synchronization ofchanges made to objects stored within each of the selected federatedarea and the external storage space, as previously discussed. In some ofsuch embodiments, automatic synchronization may be effected simply bytransferring a copy of an object modified within one of the twolocations to the other of the two locations such that both locations arecaused to have identical objects.

As with the aforedescribed automatic transfers between federated areas,any of a variety of conditions may be specified as the trigger forcausing such automated transfers, such as the aforementioned examples ofthe successful completion of testing of an object (e.g., a task routine)and/or of a neural network as a trigger. As an alternate example, wherethe external storage space and the selected area are both used as sharedstorage locations at which multiple developers may maintain objectsand/or portions of objects under development, the trigger may be aninstance in which an object is in someway marked or otherwise indicatedas having been completed to a degree that a developer desires to make itavailable to the other developers. Such marking may be associated with aprocess in which an object and/or changes thereto are “committed” to apool of other objects stored within either of the two locations thathave also been deemed and marked as similarly complete. Thus, upon anobject having been so marked in one of the two locations, the one ormore federated devices may cause a copy thereof to be transferred toother of the two locations and similarly marked such that the fact ofthat object (or changes made thereto) having been “committed” is madeevident at both locations.

It should be noted that, unlike the one or more federated areasmaintained by the one or more federated devices with the aforementionedset of rules that enforce conditions on when objects may be storedwithin federated area(s) and/or removed therefrom, there may be no suchset of rules that are employed to provide similar restrictions for suchan external storage space. Thus, synchronization between a selectedfederated area and such an external storage space may necessitateproviding the ability to at least temporarily suspend the enforcement ofsuch rules for the selected federated area, at least where new objectsand/or changes to objects are effected by the occurrence of transfersfrom the external storage space and to the selected federated area. Itmay be that the formation of such a relationship between a federatedarea and an external storage space is limited to a private federatedarea so as to avoid having a federated area in which there is such asuspension of rules that also becomes a federated area from which otherfederated areas may inherit objects. Alternatively or additionally, itmay be that a portion of a federated area is designated as a transferarea that becomes the portion of that federated area in which thecontents therein are kept synchronized with the external storage space.

In such example embodiments as are described above in which the selectedfederated area and the external storage space are both employed asshared storage spaces to enable the collaborative development of objectsamong multiple developers, such transfers to synchronize the conditionsof objects therebetween may be performed bi-directionally such thatchanges to objects made within either location are reflected in thecorresponding objects within the other location. As will be explained ingreater detail, in embodiments in which such a collaboration is intendedto result in the generation of a full set of objects needed to perform ajob flow within the one or more federated areas, it may be that arelimits on the bi-directionality of the exchanges such that, for example,job flow definitions may be exchanged bi-directionally, but not taskroutines. This may be the case where the developers who access theexternal storage space, but not the one or more federated areas, may begenerating task routines and/or job flow definitions in a differentprogramming language from the developers who access the one or morefederated areas. Thus, in such a collaboration, task routines that maybe accepted from the external storage space through such asynchronization relationship, but no task routines developed within theone or more federated areas may be transmitted back to the externalstorage space. In contrast, the job flow definition that defines the jobflow under development may be transferred in either direction between toenable both groups of developers to be guided by the definition of thejob flow therein and/or to enable either of these two groups ofdevelopers to modify it as the job flow evolves throughout itsdevelopment.

There may be other embodiments in which an external storage space isused to disseminate new objects among multiple persons and/or entitiesthat do not have access to the one or more federated areas, and thetransfers to synchronize the conditions of objects therebetween may beentirely unidirectional from the designated federated area and to theexternal storage space. More specifically, it may be that fullydeveloped and tested objects deemed ready for widespread disseminationfor use by others are caused to be stored within the designatedfederated area (or within a portion thereof that is designated as atransfer area), and the fact that such an object has been stored thereinmay be used as the trigger to cause the automatic transfer of a copy ofthat object to the external storage space, while in contrast, there maybe no automated transfers of objects back to the federated area from theexternal storage space.

Regardless of the exact manner in which objects are received by the oneor more federated devices for storage in a federated area, it may bethat at least some of those received objects may be written in a varietyof different programming languages. More specifically, while someobjects may be received that are written in a primary programminglanguage that is normally expected to be interpreted by the one or morefederated devices during a performance of a job flow (e.g., the SASlanguage), other objects may be received that may be written in one of apre-selected set of secondary programming languages the one or morefederated devices may also be capable of interpreting during aperformance of a job flow (e.g., C, R, Python™).

As will be explained in greater detail, it may be deemed desirable toprovide support for objects written in such secondary language(s) toenable programmers who are unfamiliar with the primary language tononetheless avail themselves of the various benefits of federated areas.Additionally, supporting such secondary languages may enable programmerswho are unfamiliar with the primary language and/or the features offederated areas, the highly structured nature of federated areas and/orthe writing of programs for a many-task computing environment to stillbe able to collaborate with other programmers who are familiartherewith.

As part of supporting the use of one or more secondary programminglanguages, some limited degree of translation of programming languagesmay be performed on portions of objects received by the one or morefederated devices. More specifically, the one or more federated devicesmay automatically translate portion(s) of a job flow definition thatdefines input and/or output interfaces for each task specified as partof its job flow, and/or may translate portion(s) of a task routine thatimplement input and/or output interfaces. Such translations may be fromboth the primary programming language and any of the pre-selectedsecondary programming languages, and into a single type of intermediaterepresentation, such as an intermediate data structure or anintermediate programming language (e.g., JSON). This may enablecomparisons to be made among specifications and/or implementations ofinput and/or output interfaces to be performed, regardless of which ofthe programming languages were used to write the specifications and/orimplementations of those input and/or output interfaces. In this way,multiple programming languages are able to be accommodated while stillusing such comparisons to enforce the earlier described rules that maybe used to limit what job flow definitions and/or task routines may bepermitted to be stored within the one or more federated areas.

In some embodiments, the performance of translations from the primaryprogramming language and/or secondary programming language(s) may belimited to such translations of specifications and/or implementations ofinput and/or output interfaces into such an intermediate representationfor such comparisons. It may be deemed undesirable and/or unnecessary totranslate other portions of task routines and/or job flow definitions toperform such comparisons and/or for any other purpose.

However, in other embodiments, it may deemed desirable to performtranslations to the extent needed to derive a task routine written inthe primary programming language from a task routine written a secondaryprogramming language. This may be deemed desirable to enable developerswho are generating objects required for a job flow in the primaryprogramming language to have access to a version of the job flowdefinition that is also written in the primary programming to serve as aguide for their work and/or to enable them to make modificationsthereto. In embodiments in which it is just the portion(s) of a job flowthat define input and/or output interfaces that are written in aparticular programming language, the translation thereof into theintermediate representation (e.g., an intermediate programming language)may be used as the basis for translations between primary and secondaryprogramming languages. More specifically, where a job flow definition isreceived in which portion(s) that define input and/or output interfacesare written in a secondary programming language, the intermediaterepresentation into which those portion(s) are translated to enable theaforedescribed comparisons may also be used as the basis to generatecorresponding portion(s) that define the input and/or output interfacesin the primary language as part of a translated form of the job flowdefinition. In such embodiments, it may be translated form of the jobflow definition that is then stored, instead of the originally receivedjob flow definition.

Additionally, in such embodiments in which a translated form of a jobflow definition with input and/or output interface definitions in theprimary language may be generated from an originally received job flowdefinition that includes input and/or output interface definitions in asecondary language, it may be that such translations are performedbi-directionally as part of further supporting a collaboration among acombination of developers in which both the primary and secondarylanguages are used. More specifically, where a job flow definition inwhich input and/or output interface definitions are written in theprimary language, an intermediate representation into which thoseportion(s) are translated to enable the aforedescribed comparisons mayalso be used as the basis to generate corresponding input and/or outputinterface definitions in a secondary programming language. Such areverse translation may be performed regardless of whether the job flowdefinition with input and/or output definitions was originally writtenin the primary programming language, or was translated into the primaryprogramming language from an originally received job flow definitionwritten in a secondary programming language. This may be deemeddesirable to enable developers who are generating objects required for ajob flow in a secondary programming language to have access to a versionof the job flow definition that is also written in the secondaryprogramming to serve as a guide for their work and/or to enable them tomake modifications thereto.

By providing such translations of a job flow definition back and forthbetween the primary programming language and a secondary programminglanguage, either the developers who write in the primary programminglanguage or the developers who write in the secondary programminglanguage are able to read and/or edit the job flow definition in theirchosen programming language. In this way, the developers using thesecondary programming language are put on a more equal footing ascollaborators with the developers using the primary programming languageas developers of either group are able to participate in shaping thedefinition of the job flow to which both groups are contributingobjects.

As previously discussed, in some embodiments, a job flow definition mayadditionally include executable GUI instructions to implement a GUIinterface that is to be provided during a performance of the job flowthat is defined therein. In such embodiments, it may be deemed desirableto provide more extensive translation capabilities to enable thetranslation of GUI instructions between programming languages as part ofproviding a translated form of a job flow definition with input and/oroutput definitions, and also GUI instructions, written in the primaryprogramming language from a received job flow definition with inputand/or output definitions, and also GUI instructions, written in asecondary programming language, and vice versa.

In various embodiments, a set of objects needed to perform an analysismay effectively be provided to the one or more federated devices in theform of a complex data structure such as a spreadsheet data structure.Such a data structure may contain the equivalent of one or more datasets organized as two-dimensional arrays (e.g., tables) therein, maycontain one or more calculations of the analysis organized as multipleequations that may each be stored in a separate row, and/or may specifyone or more graphs that are to be presented based on a performance ofthe analysis. The one or more federated devices may interpret such adata structure to derive therefrom the set of objects needed to performthe analysis defined within the data structure as a job flow in whichthe analysis is divided into tasks that are each performed as a resultof executing a corresponding task routine.

More precisely, the multiple equations within the data structure may beanalyzed, along with the organization of the data into one or moretwo-dimensional arrays within the data structure, to derive definitionsof input and output interfaces for each of the equations and to identifyeach distinct data object. The multiple equations may also be analyzed,in view of the derived input and/or output interface definitions, toidentify the dependencies thereamong. Various checks may be made forinstances of mismatched interfaces, missing data that is required asinput and/or unused data to determine whether the contents of the datastructure set forth analysis a complete analysis that is able to beperformed. Presuming that the analysis is determined to be performable,a job flow definition may be derived based on the input and/or outputinterfaces and the identified dependencies in which each of theequations may be treated as a task of the job flow that is defined bythe job flow definition. Each equation may be parsed to generate acorresponding task routine to perform the task of that equation, asspecified in the job flow definition. Each identified data object may begenerated from a two-dimensional array or a portion of a two-dimensionalarray within the data structure. This set of generated data objects maythen be stored within the federated area into which it was requestedthat the data structure be stored. In some embodiments, the datastructure, itself, may also be stored within the federated area as ameasure to provide accountability for the quality of the conversion ofthe data structure into the set of objects.

In various embodiments, one or more of comments descriptive of inputand/or output interfaces within one or more task routines, portions ofinstructions within one or more task routines that implement inputand/or output interfaces, and specifications of input and/or outputinterfaces provided in one or more job flow definitions may be used togenerate a directed acyclic graph (DAG) of one or more task routinesand/or of a job flow. More precisely, such information may be used tobuild any of a variety of data structure(s) that correlate inputs and/oroutputs to tasks and/or the task routines that are to perform thosetasks, and from which a DAG for one or more task routines and/or a jobflow may be generated and/or visually presented. In some embodiments,such a data structure may include script generated in a markup languageand/or a block of programming code for each task or task routine (e.g.,a macro employing syntax from any of a variety of programminglanguages). Regardless of the form of the data structure(s) that aregenerated, such a data structure may also specify the task routineidentifier assigned to each task routine and/or the flow task identifieridentifying the task performed by each task routine.

Which one or more task routines are to be included in such a DAG may bespecified in any of a variety of ways. By way of example, a request maybe received for a DAG that includes one or more tasks or task routinesthat are explicitly identified by their respective flow task identifiersand/or task routine identifiers. By way of another example, a requestmay be received for a DAG that includes all of the task routinescurrently stored within a federated area that may be specified by a URL.By way of still another example, a request may be received for a DAGthat includes task routines for all of the tasks identified within aspecified job flow definition. And, by way of yet another example, arequest may be received for a DAG that includes all of the task routinesspecified by their identifiers in an instance log of a previousperformance of a job flow. Regardless of the exact manner in which oneor more tasks and/or task routines may be specified in a request forinclusion within a DAG, each task routine that is directly identified orthat is specified indirectly through the flow task identifier of thetask it performs may be searched for within one or more federated areasas earlier described.

In situations in which a DAG is requested that is to include multipletasks and/or task routines, the DAG may be generated to indicate anydependencies thereamong. In some embodiments, a visualization of the DAGmay be generated to provide a visual indication of such a dependency,such as a line, arrow, color coding, graphical symbols and/or other formof visual connector indicative of the dependency may be generated withinthe visualization to visually link an output of the one task routine toan input of the other. In embodiments in which the parsing of taskroutines and/or of job flows includes comparisons between pieces ofinformation that may result in the detection of discrepancies in suchdetails as dependencies among tasks and/or among task routines, suchdiscrepancies may be visually indicated in a DAG in any of a variety ofways. By way of example, a DAG may be generated to indicate suchdiscrepancies with color coding, graphical symbols and/or other form ofvisual indicator positioned at or adjacent to the graphical depiction ofthe affected input or output in the DAG. Such a visual indicator maythereby serve as a visual prompt to personnel viewing the DAG to accessthe affected task routine(s) and/or affected job flow definition toexamine and/or correct the discrepancy. Alternatively or additionally,at least a pair of alternate DAGs may be generated, and personnel may beprovided with a user interface (UI) that enables “toggling” therebetweenand/or a side-by-side comparison, where one DAG is based on the detailsof inputs and/or outputs provided by comments while another DAG is basedon the manner in which those details are actually implemented inexecutable code.

In some embodiments, with a DAG generated and visually presented forviewing by personnel involved in the development of new task routinesand/or new job flow definitions, such personnel may be provided with aUI that enables editing of the DAG. More specifically, a UI may beprovided that enables depicted dependencies between inputs and outputsof task routines to be removed or otherwise changed, and/or that enablesnew dependencies to be added. Through the provision of such a UI,personnel involved in the development of new task routines and/or newjob flow definitions may be able to define a new job flow by modifying aDAG generated from one or more task routines. Indeed, the one or moretask routines may be selected for inclusion in a DAG for the purpose ofhaving them available in the DAG for inclusion in the new job flow.Regardless of whether or not a DAG generated from one or more taskroutines is edited as has just been described, a UI may be provided toenable personnel to choose to save the DAG as a new job flow definition.Regardless of whether the DAG is saved for use as a job flow definition,or simply to retain the DAG for future reference, the DAG may be storedas a script generated in a process description language such as businessprocess model and notation (BPMN) promulgated by the Object ManagementGroup of Needham, Mass., USA.

As an alternative to receiving a request to generate a DAG based on atleast one or more task routines, a request may be received by one ormore federated devices from another device to provide the other devicewith objects needed to enable the other device to so generate a DAG. Insome embodiments, such a request may be treated in a manner similar toearlier described requests to retrieve objects needed to enable anotherdevice to perform a job flow with most recent versions of task routinesor to repeat a past performance of a job flow, as documented by aninstance log. However, in some embodiments, the data structure(s)generated from parsing task routines and/or a job flow definition may betransmitted to the other device in lieu of transmitting the taskroutines, themselves. This may be deemed desirable as a mechanism toreduce the quantity of information transmitted to the other device forits use in generating a DAG.

Regardless of whether a requested DAG is to include a depiction of asingle task routine or of multiple task routines, it may be that, priorto the receipt of the request for the DAG, one or more of the taskroutines to be depicted therein may have been test executed to observetheir input/output behavior within a container environment as previouslydescribed. As also previously discussed, an indication of theinput/output behavior observed under such container environmentconditions for each task routine so tested may be stored in any of avariety of ways to enable its subsequent retrieval. It may be that anindication of the input/output behavior that was observed may bepositioned next to the depiction of a corresponding task routine withinthe requested DAG.

With general reference to notations and nomenclature used herein,portions of the detailed description that follows may be presented interms of program procedures executed by a processor of a machine or ofmultiple networked machines. These procedural descriptions andrepresentations are used by those skilled in the art to most effectivelyconvey the substance of their work to others skilled in the art. Aprocedure is here, and generally, conceived to be a self-consistentsequence of operations leading to a desired result. These operations arethose requiring physical manipulations of physical quantities. Usually,though not necessarily, these quantities take the form of electrical,magnetic or optical communications capable of being stored, transferred,combined, compared, and otherwise manipulated. It proves convenient attimes, principally for reasons of common usage, to refer to what iscommunicated as bits, values, elements, symbols, characters, terms,numbers, or the like. It should be noted, however, that all of these andsimilar terms are to be associated with the appropriate physicalquantities and are merely convenient labels applied to those quantities.

Further, these manipulations are often referred to in terms, such asadding or comparing, which are commonly associated with mentaloperations performed by a human operator. However, no such capability ofa human operator is necessary, or desirable in most cases, in any of theoperations described herein that form part of one or more embodiments.Rather, these operations are machine operations. Useful machines forperforming operations of various embodiments include machinesselectively activated or configured by a routine stored within that iswritten in accordance with the teachings herein, and/or includeapparatus specially constructed for the required purpose. Variousembodiments also relate to apparatus or systems for performing theseoperations. These apparatus may be specially constructed for therequired purpose or may include a general purpose computer. The requiredstructure for a variety of these machines will appear from thedescription given.

Reference is now made to the drawings, wherein like reference numeralsare used to refer to like elements throughout. In the followingdescription, for purposes of explanation, numerous specific details areset forth in order to provide a thorough understanding thereof. It maybe evident, however, that the novel embodiments can be practiced withoutthese specific details. In other instances, well known structures anddevices are shown in block diagram form in order to facilitate adescription thereof. The intention is to cover all modifications,equivalents, and alternatives within the scope of the claims.

Systems depicted in some of the figures may be provided in variousconfigurations. In some embodiments, the systems may be configured as adistributed system where one or more components of the system aredistributed across one or more networks in a cloud computing systemand/or a fog computing system.

FIG. 1 is a block diagram that provides an illustration of the hardwarecomponents of a data transmission network 100, according to embodimentsof the present technology. Data transmission network 100 is aspecialized computer system that may be used for processing largeamounts of data where a large number of computer processing cycles arerequired.

Data transmission network 100 may also include computing environment114. Computing environment 114 may be a specialized computer or othermachine that processes the data received within the data transmissionnetwork 100. Data transmission network 100 also includes one or morenetwork devices 102. Network devices 102 may include client devices thatattempt to communicate with computing environment 114. For example,network devices 102 may send data to the computing environment 114 to beprocessed, may send signals to the computing environment 114 to controldifferent aspects of the computing environment or the data it isprocessing, among other reasons. Network devices 102 may interact withthe computing environment 114 through a number of ways, such as, forexample, over one or more networks 108. As shown in FIG. 1, computingenvironment 114 may include one or more other systems. For example,computing environment 114 may include a database system 118 and/or acommunications grid 120.

In other embodiments, network devices may provide a large amount ofdata, either all at once or streaming over a period of time (e.g., usingevent stream processing (ESP), described further with respect to FIGS.8-10), to the computing environment 114 via networks 108. For example,network devices 102 may include network computers, sensors, databases,or other devices that may transmit or otherwise provide data tocomputing environment 114. For example, network devices may includelocal area network devices, such as routers, hubs, switches, or othercomputer networking devices. These devices may provide a variety ofstored or generated data, such as network data or data specific to thenetwork devices themselves. Network devices may also include sensorsthat monitor their environment or other devices to collect dataregarding that environment or those devices, and such network devicesmay provide data they collect over time. Network devices may alsoinclude devices within the internet of things, such as devices within ahome automation network. Some of these devices may be referred to asedge devices, and may involve edge computing circuitry. Data may betransmitted by network devices directly to computing environment 114 orto network-attached data stores, such as network-attached data stores110 for storage so that the data may be retrieved later by the computingenvironment 114 or other portions of data transmission network 100.

Data transmission network 100 may also include one or morenetwork-attached data stores 110. Network-attached data stores 110 areused to store data to be processed by the computing environment 114 aswell as any intermediate or final data generated by the computing systemin non-volatile memory. However in certain embodiments, theconfiguration of the computing environment 114 allows its operations tobe performed such that intermediate and final data results can be storedsolely in volatile memory (e.g., RAM), without a requirement thatintermediate or final data results be stored to non-volatile types ofmemory (e.g., disk). This can be useful in certain situations, such aswhen the computing environment 114 receives ad hoc queries from a userand when responses, which are generated by processing large amounts ofdata, need to be generated on-the-fly. In this non-limiting situation,the computing environment 114 may be configured to retain the processedinformation within memory so that responses can be generated for theuser at different levels of detail as well as allow a user tointeractively query against this information.

Network-attached data stores may store a variety of different types ofdata organized in a variety of different ways and from a variety ofdifferent sources. For example, network-attached data storage mayinclude storage other than primary storage located within computingenvironment 114 that is directly accessible by processors locatedtherein. Network-attached data storage may include secondary, tertiaryor auxiliary storage, such as large hard drives, servers, virtualmemory, among other types. Storage devices may include portable ornon-portable storage devices, optical storage devices, and various othermediums capable of storing, containing data. A machine-readable storagemedium or computer-readable storage medium may include a non-transitorymedium in which data can be stored and that does not include carrierwaves and/or transitory electronic signals. Examples of a non-transitorymedium may include, for example, a magnetic disk or tape, opticalstorage media such as compact disk or digital versatile disk, flashmemory, memory or memory devices. A computer-program product may includecode and/or machine-executable instructions that may represent aprocedure, a function, a subprogram, a program, a routine, a subroutine,a module, a software package, a class, or any combination ofinstructions, data structures, or program statements. A code segment maybe coupled to another code segment or a hardware circuit by passingand/or receiving information, data, arguments, parameters, or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, amongothers. Furthermore, the data stores may hold a variety of differenttypes of data. For example, network-attached data stores 110 may holdunstructured (e.g., raw) data, such as manufacturing data (e.g., adatabase containing records identifying products being manufactured withparameter data for each product, such as colors and models) or productsales databases (e.g., a database containing individual data recordsidentifying details of individual product sales).

The unstructured data may be presented to the computing environment 114in different forms such as a flat file or a conglomerate of datarecords, and may have data values and accompanying time stamps. Thecomputing environment 114 may be used to analyze the unstructured datain a variety of ways to determine the best way to structure (e.g.,hierarchically) that data, such that the structured data is tailored toa type of further analysis that a user wishes to perform on the data.For example, after being processed, the unstructured time stamped datamay be aggregated by time (e.g., into daily time period units) togenerate time series data and/or structured hierarchically according toone or more dimensions (e.g., parameters, attributes, and/or variables).For example, data may be stored in a hierarchical data structure, suchas a ROLAP OR MOLAP database, or may be stored in another tabular form,such as in a flat-hierarchy form.

Data transmission network 100 may also include one or more server farms106. Computing environment 114 may route select communications or datato the one or more sever farms 106 or one or more servers within theserver farms. Server farms 106 can be configured to provide informationin a predetermined manner. For example, server farms 106 may access datato transmit in response to a communication. Server farms 106 may beseparately housed from each other device within data transmissionnetwork 100, such as computing environment 114, and/or may be part of adevice or system.

Server farms 106 may host a variety of different types of dataprocessing as part of data transmission network 100. Server farms 106may receive a variety of different data from network devices, fromcomputing environment 114, from cloud network 116, or from othersources. The data may have been obtained or collected from one or moresensors, as inputs from a control database, or may have been received asinputs from an external system or device. Server farms 106 may assist inprocessing the data by turning raw data into processed data based on oneor more rules implemented by the server farms. For example, sensor datamay be analyzed to determine changes in an environment over time or inreal-time.

Data transmission network 100 may also include one or more cloudnetworks 116. Cloud network 116 may include a cloud infrastructuresystem that provides cloud services. In certain embodiments, servicesprovided by the cloud network 116 may include a host of services thatare made available to users of the cloud infrastructure system on demandCloud network 116 is shown in FIG. 1 as being connected to computingenvironment 114 (and therefore having computing environment 114 as itsclient or user), but cloud network 116 may be connected to or utilizedby any of the devices in FIG. 1. Services provided by the cloud networkcan dynamically scale to meet the needs of its users. The cloud network116 may include one or more computers, servers, and/or systems. In someembodiments, the computers, servers, and/or systems that make up thecloud network 116 are different from the user's own on-premisescomputers, servers, and/or systems. For example, the cloud network 116may host an application, and a user may, via a communication networksuch as the Internet, on demand, order and use the application.

While each device, server and system in FIG. 1 is shown as a singledevice, it will be appreciated that multiple devices may instead beused. For example, a set of network devices can be used to transmitvarious communications from a single user, or remote server 140 mayinclude a server stack. As another example, data may be processed aspart of computing environment 114.

Each communication within data transmission network 100 (e.g., betweenclient devices, between servers 106 and computing environment 114 orbetween a server and a device) may occur over one or more networks 108.Networks 108 may include one or more of a variety of different types ofnetworks, including a wireless network, a wired network, or acombination of a wired and wireless network. Examples of suitablenetworks include the Internet, a personal area network, a local areanetwork (LAN), a wide area network (WAN), or a wireless local areanetwork (WLAN). A wireless network may include a wireless interface orcombination of wireless interfaces. As an example, a network in the oneor more networks 108 may include a short-range communication channel,such as a BLUETOOTH® communication channel or a BLUETOOTH® Low Energycommunication channel. A wired network may include a wired interface.The wired and/or wireless networks may be implemented using routers,access points, bridges, gateways, or the like, to connect devices in thenetwork 114, as will be further described with respect to FIG. 2. Theone or more networks 108 can be incorporated entirely within or caninclude an intranet, an extranet, or a combination thereof. In oneembodiment, communications between two or more systems and/or devicescan be achieved by a secure communications protocol, such as securesockets layer (SSL) or transport layer security (TLS). In addition, dataand/or transactional details may be encrypted.

Some aspects may utilize the Internet of Things (IoT), where things(e.g., machines, devices, phones, sensors) can be connected to networksand the data from these things can be collected and processed within thethings and/or external to the things. For example, the IoT can includesensors in many different devices, and high value analytics can beapplied to identify hidden relationships and drive increasedefficiencies. This can apply to both big data analytics and real-time(e.g., ESP) analytics. This will be described further below with respectto FIG. 2.

As noted, computing environment 114 may include a communications grid120 and a transmission network database system 118. Communications grid120 may be a grid-based computing system for processing large amounts ofdata. The transmission network database system 118 may be for managing,storing, and retrieving large amounts of data that are distributed toand stored in the one or more network-attached data stores 110 or otherdata stores that reside at different locations within the transmissionnetwork database system 118. The compute nodes in the grid-basedcomputing system 120 and the transmission network database system 118may share the same processor hardware, such as processors that arelocated within computing environment 114.

FIG. 2 illustrates an example network including an example set ofdevices communicating with each other over an exchange system and via anetwork, according to embodiments of the present technology. As noted,each communication within data transmission network 100 may occur overone or more networks. System 200 includes a network device 204configured to communicate with a variety of types of client devices, forexample client devices 230, over a variety of types of communicationchannels.

As shown in FIG. 2, network device 204 can transmit a communication overa network (e.g., a cellular network via a base station 210). Thecommunication can be routed to another network device, such as networkdevices 205-209, via base station 210. The communication can also berouted to computing environment 214 via base station 210. For example,network device 204 may collect data either from its surroundingenvironment or from other network devices (such as network devices205-209) and transmit that data to computing environment 214.

Although network devices 204-209 are shown in FIG. 2 as a mobile phone,laptop computer, tablet computer, temperature sensor, motion sensor, andaudio sensor respectively, the network devices may be or include sensorsthat are sensitive to detecting aspects of their environment. Forexample, the network devices may include sensors such as water sensors,power sensors, electrical current sensors, chemical sensors, opticalsensors, pressure sensors, geographic or position sensors (e.g., GPS),velocity sensors, acceleration sensors, flow rate sensors, among others.Examples of characteristics that may be sensed include force, torque,load, strain, position, temperature, air pressure, fluid flow, chemicalproperties, resistance, electromagnetic fields, radiation, irradiance,proximity, acoustics, moisture, distance, speed, vibrations,acceleration, electrical potential, electrical current, among others.The sensors may be mounted to various components used as part of avariety of different types of systems (e.g., an oil drilling operation).The network devices may detect and record data related to theenvironment that it monitors, and transmit that data to computingenvironment 214.

As noted, one type of system that may include various sensors thatcollect data to be processed and/or transmitted to a computingenvironment according to certain embodiments includes an oil drillingsystem. For example, the one or more drilling operation sensors mayinclude surface sensors that measure a hook load, a fluid rate, atemperature and a density in and out of the wellbore, a standpipepressure, a surface torque, a rotation speed of a drill pipe, a rate ofpenetration, a mechanical specific energy, etc. and downhole sensorsthat measure a rotation speed of a bit, fluid densities, downholetorque, downhole vibration (axial, tangential, lateral), a weightapplied at a drill bit, an annular pressure, a differential pressure, anazimuth, an inclination, a dog leg severity, a measured depth, avertical depth, a downhole temperature, etc. Besides the raw datacollected directly by the sensors, other data may include parameterseither developed by the sensors or assigned to the system by a client orother controlling device. For example, one or more drilling operationcontrol parameters may control settings such as a mud motor speed toflow ratio, a bit diameter, a predicted formation top, seismic data,weather data, etc. Other data may be generated using physical modelssuch as an earth model, a weather model, a seismic model, a bottom holeassembly model, a well plan model, an annular friction model, etc. Inaddition to sensor and control settings, predicted outputs, of forexample, the rate of penetration, mechanical specific energy, hook load,flow in fluid rate, flow out fluid rate, pump pressure, surface torque,rotation speed of the drill pipe, annular pressure, annular frictionpressure, annular temperature, equivalent circulating density, etc. mayalso be stored in the data warehouse.

In another example, another type of system that may include varioussensors that collect data to be processed and/or transmitted to acomputing environment according to certain embodiments includes a homeautomation or similar automated network in a different environment, suchas an office space, school, public space, sports venue, or a variety ofother locations. Network devices in such an automated network mayinclude network devices that allow a user to access, control, and/orconfigure various home appliances located within the user's home (e.g.,a television, radio, light, fan, humidifier, sensor, microwave, iron,and/or the like), or outside of the user's home (e.g., exterior motionsensors, exterior lighting, garage door openers, sprinkler systems, orthe like). For example, network device 102 may include a home automationswitch that may be coupled with a home appliance. In another embodiment,a network device can allow a user to access, control, and/or configuredevices, such as office-related devices (e.g., copy machine, printer, orfax machine), audio and/or video related devices (e.g., a receiver, aspeaker, a projector, a DVD player, or a television), media-playbackdevices (e.g., a compact disc player, a CD player, or the like),computing devices (e.g., a home computer, a laptop computer, a tablet, apersonal digital assistant (PDA), a computing device, or a wearabledevice), lighting devices (e.g., a lamp or recessed lighting), devicesassociated with a security system, devices associated with an alarmsystem, devices that can be operated in an automobile (e.g., radiodevices, navigation devices), and/or the like. Data may be collectedfrom such various sensors in raw form, or data may be processed by thesensors to create parameters or other data either developed by thesensors based on the raw data or assigned to the system by a client orother controlling device.

In another example, another type of system that may include varioussensors that collect data to be processed and/or transmitted to acomputing environment according to certain embodiments includes a poweror energy grid. A variety of different network devices may be includedin an energy grid, such as various devices within one or more powerplants, energy farms (e.g., wind farm, solar farm, among others) energystorage facilities, factories, homes and businesses of consumers, amongothers. One or more of such devices may include one or more sensors thatdetect energy gain or loss, electrical input or output or loss, and avariety of other efficiencies. These sensors may collect data to informusers of how the energy grid, and individual devices within the grid,may be functioning and how they may be made more efficient.

Network device sensors may also perform processing on data it collectsbefore transmitting the data to the computing environment 114, or beforedeciding whether to transmit data to the computing environment 114. Forexample, network devices may determine whether data collected meetscertain rules, for example by comparing data or values calculated fromthe data and comparing that data to one or more thresholds. The networkdevice may use this data and/or comparisons to determine if the datashould be transmitted to the computing environment 214 for further useor processing.

Computing environment 214 may include machines 220 and 240. Althoughcomputing environment 214 is shown in FIG. 2 as having two machines, 220and 240, computing environment 214 may have only one machine or may havemore than two machines. The machines that make up computing environment214 may include specialized computers, servers, or other machines thatare configured to individually and/or collectively process large amountsof data. The computing environment 214 may also include storage devicesthat include one or more databases of structured data, such as dataorganized in one or more hierarchies, or unstructured data. Thedatabases may communicate with the processing devices within computingenvironment 214 to distribute data to them. Since network devices maytransmit data to computing environment 214, that data may be received bythe computing environment 214 and subsequently stored within thosestorage devices. Data used by computing environment 214 may also bestored in data stores 235, which may also be a part of or connected tocomputing environment 214.

Computing environment 214 can communicate with various devices via oneor more routers 225 or other inter-network or intra-network connectioncomponents. For example, computing environment 214 may communicate withdevices 230 via one or more routers 225. Computing environment 214 maycollect, analyze and/or store data from or pertaining to communications,client device operations, client rules, and/or user-associated actionsstored at one or more data stores 235. Such data may influencecommunication routing to the devices within computing environment 214,how data is stored or processed within computing environment 214, amongother actions.

Notably, various other devices can further be used to influencecommunication routing and/or processing between devices within computingenvironment 214 and with devices outside of computing environment 214.For example, as shown in FIG. 2, computing environment 214 may include aweb server 240. Thus, computing environment 214 can retrieve data ofinterest, such as client information (e.g., product information, clientrules, etc.), technical product details, news, current or predictedweather, and so on.

In addition to computing environment 214 collecting data (e.g., asreceived from network devices, such as sensors, and client devices orother sources) to be processed as part of a big data analytics project,it may also receive data in real time as part of a streaming analyticsenvironment. As noted, data may be collected using a variety of sourcesas communicated via different kinds of networks or locally. Such datamay be received on a real-time streaming basis. For example, networkdevices may receive data periodically from network device sensors as thesensors continuously sense, monitor and track changes in theirenvironments. Devices within computing environment 214 may also performpre-analysis on data it receives to determine if the data receivedshould be processed as part of an ongoing project. The data received andcollected by computing environment 214, no matter what the source ormethod or timing of receipt, may be processed over a period of time fora client to determine results data based on the client's needs andrules.

FIG. 3 illustrates a representation of a conceptual model of acommunications protocol system, according to embodiments of the presenttechnology. More specifically, FIG. 3 identifies operation of acomputing environment in an Open Systems Interaction model thatcorresponds to various connection components. The model 300 shows, forexample, how a computing environment, such as computing environment 314(or computing environment 214 in FIG. 2) may communicate with otherdevices in its network, and control how communications between thecomputing environment and other devices are executed and under whatconditions.

The model can include layers 301-307. The layers are arranged in astack. Each layer in the stack serves the layer one level higher than it(except for the application layer, which is the highest layer), and isserved by the layer one level below it (except for the physical layer,which is the lowest layer). The physical layer is the lowest layerbecause it receives and transmits raw bites of data, and is the farthestlayer from the user in a communications system. On the other hand, theapplication layer is the highest layer because it interacts directlywith a software application.

As noted, the model includes a physical layer 301. Physical layer 301represents physical communication, and can define parameters of thatphysical communication. For example, such physical communication maycome in the form of electrical, optical, or electromagnetic signals.Physical layer 301 also defines protocols that may controlcommunications within a data transmission network.

Link layer 302 defines links and mechanisms used to transmit (i.e.,move) data across a network. The link layer 302 manages node-to-nodecommunications, such as within a grid computing environment. Link layer302 can detect and correct errors (e.g., transmission errors in thephysical layer 301). Link layer 302 can also include a media accesscontrol (MAC) layer and logical link control (LLC) layer.

Network layer 303 defines the protocol for routing within a network. Inother words, the network layer coordinates transferring data acrossnodes in a same network (e.g., such as a grid computing environment).Network layer 303 can also define the processes used to structure localaddressing within the network.

Transport layer 304 can manage the transmission of data and the qualityof the transmission and/or receipt of that data. Transport layer 304 canprovide a protocol for transferring data, such as, for example, aTransmission Control Protocol (TCP). Transport layer 304 can assembleand disassemble data frames for transmission. The transport layer canalso detect transmission errors occurring in the layers below it.

Session layer 305 can establish, maintain, and manage communicationconnections between devices on a network. In other words, the sessionlayer controls the dialogues or nature of communications between networkdevices on the network. The session layer may also establishcheckpointing, adjournment, termination, and restart procedures.

Presentation layer 306 can provide translation for communicationsbetween the application and network layers. In other words, this layermay encrypt, decrypt and/or format data based on data types and/orencodings known to be accepted by an application or network layer.

Application layer 307 interacts directly with software applications andend users, and manages communications between them. Application layer307 can identify destinations, local resource states or availabilityand/or communication content or formatting using the applications.

Intra-network connection components 321 and 322 are shown to operate inlower levels, such as physical layer 301 and link layer 302,respectively. For example, a hub can operate in the physical layer, aswitch can operate in the link layer, and a router can operate in thenetwork layer. Inter-network connection components 323 and 328 are shownto operate on higher levels, such as layers 303-307. For example,routers can operate in the network layer and network devices can operatein the transport, session, presentation, and application layers.

As noted, a computing environment 314 can interact with and/or operateon, in various embodiments, one, more, all or any of the various layers.For example, computing environment 314 can interact with a hub (e.g.,via the link layer) so as to adjust which devices the hub communicateswith. The physical layer may be served by the link layer, so it mayimplement such data from the link layer. For example, the computingenvironment 314 may control which devices it will receive data from. Forexample, if the computing environment 314 knows that a certain networkdevice has turned off, broken, or otherwise become unavailable orunreliable, the computing environment 314 may instruct the hub toprevent any data from being transmitted to the computing environment 314from that network device. Such a process may be beneficial to avoidreceiving data that is inaccurate or that has been influenced by anuncontrolled environment. As another example, computing environment 314can communicate with a bridge, switch, router or gateway and influencewhich device within the system (e.g., system 200) the component selectsas a destination. In some embodiments, computing environment 314 caninteract with various layers by exchanging communications with equipmentoperating on a particular layer by routing or modifying existingcommunications. In another embodiment, such as in a grid computingenvironment, a node may determine how data within the environment shouldbe routed (e.g., which node should receive certain data) based oncertain parameters or information provided by other layers within themodel.

As noted, the computing environment 314 may be a part of acommunications grid environment, the communications of which may beimplemented as shown in the protocol of FIG. 3. For example, referringback to FIG. 2, one or more of machines 220 and 240 may be part of acommunications grid computing environment. A gridded computingenvironment may be employed in a distributed system with non-interactiveworkloads where data resides in memory on the machines, or computenodes. In such an environment, analytic code, instead of a databasemanagement system, controls the processing performed by the nodes. Datais co-located by pre-distributing it to the grid nodes, and the analyticcode on each node loads the local data into memory. Each node may beassigned a particular task such as a portion of a processing project, orto organize or control other nodes within the grid.

FIG. 4 illustrates a communications grid computing system 400 includinga variety of control and worker nodes, according to embodiments of thepresent technology.

Communications grid computing system 400 includes three control nodesand one or more worker nodes. Communications grid computing system 400includes control nodes 402, 404, and 406. The control nodes arecommunicatively connected via communication paths 451, 453, and 455.Therefore, the control nodes may transmit information (e.g., related tothe communications grid or notifications), to and receive informationfrom each other. Although communications grid computing system 400 isshown in FIG. 4 as including three control nodes, the communicationsgrid may include more or less than three control nodes.

Communications grid computing system (or just “communications grid”) 400also includes one or more worker nodes. Shown in FIG. 4 are six workernodes 410-420. Although FIG. 4 shows six worker nodes, a communicationsgrid according to embodiments of the present technology may include moreor less than six worker nodes. The number of worker nodes included in acommunications grid may be dependent upon how large the project or dataset is being processed by the communications grid, the capacity of eachworker node, the time designated for the communications grid to completethe project, among others. Each worker node within the communicationsgrid 400 may be connected (wired or wirelessly, and directly orindirectly) to control nodes 402-406. Therefore, each worker node mayreceive information from the control nodes (e.g., an instruction toperform work on a project) and may transmit information to the controlnodes (e.g., a result from work performed on a project). Furthermore,worker nodes may communicate with each other (either directly orindirectly). For example, worker nodes may transmit data between eachother related to a job being performed or an individual task within ajob being performed by that worker node. However, in certainembodiments, worker nodes may not, for example, be connected(communicatively or otherwise) to certain other worker nodes. In anembodiment, worker nodes may only be able to communicate with thecontrol node that controls it, and may not be able to communicate withother worker nodes in the communications grid, whether they are otherworker nodes controlled by the control node that controls the workernode, or worker nodes that are controlled by other control nodes in thecommunications grid.

A control node may connect with an external device with which thecontrol node may communicate (e.g., a grid user, such as a server orcomputer, may connect to a controller of the grid). For example, aserver or computer may connect to control nodes and may transmit aproject or job to the node. The project may include a data set. The dataset may be of any size. Once the control node receives such a projectincluding a large data set, the control node may distribute the data setor projects related to the data set to be performed by worker nodes.Alternatively, for a project including a large data set, the data setmay be received or stored by a machine other than a control node (e.g.,a HADOOP® standard-compliant data node employing the HADOOP® DistributedFile System, or HDFS).

Control nodes may maintain knowledge of the status of the nodes in thegrid (i.e., grid status information), accept work requests from clients,subdivide the work across worker nodes, coordinate the worker nodes,among other responsibilities. Worker nodes may accept work requests froma control node and provide the control node with results of the workperformed by the worker node. A grid may be started from a single node(e.g., a machine, computer, server, etc.). This first node may beassigned or may start as the primary control node that will control anyadditional nodes that enter the grid.

When a project is submitted for execution (e.g., by a client or acontroller of the grid) it may be assigned to a set of nodes. After thenodes are assigned to a project, a data structure (i.e., a communicator)may be created. The communicator may be used by the project forinformation to be shared between the project code running on each node.A communication handle may be created on each node. A handle, forexample, is a reference to the communicator that is valid within asingle process on a single node, and the handle may be used whenrequesting communications between nodes.

A control node, such as control node 402, may be designated as theprimary control node. A server, computer or other external device mayconnect to the primary control node. Once the control node receives aproject, the primary control node may distribute portions of the projectto its worker nodes for execution. For example, when a project isinitiated on communications grid 400, primary control node 402 controlsthe work to be performed for the project in order to complete theproject as requested or instructed. The primary control node maydistribute work to the worker nodes based on various factors, such aswhich subsets or portions of projects may be completed most efficientlyand in the correct amount of time. For example, a worker node mayperform analysis on a portion of data that is already local (e.g.,stored on) the worker node. The primary control node also coordinatesand processes the results of the work performed by each worker nodeafter each worker node executes and completes its job. For example, theprimary control node may receive a result from one or more worker nodes,and the control node may organize (e.g., collect and assemble) theresults received and compile them to produce a complete result for theproject received from the end user.

Any remaining control nodes, such as control nodes 404 and 406, may beassigned as backup control nodes for the project. In an embodiment,backup control nodes may not control any portion of the project.Instead, backup control nodes may serve as a backup for the primarycontrol node and take over as primary control node if the primarycontrol node were to fail. If a communications grid were to include onlya single control node, and the control node were to fail (e.g., thecontrol node is shut off or breaks) then the communications grid as awhole may fail and any project or job being run on the communicationsgrid may fail and may not complete. While the project may be run again,such a failure may cause a delay (severe delay in some cases, such asovernight delay) in completion of the project. Therefore, a grid withmultiple control nodes, including a backup control node, may bebeneficial.

To add another node or machine to the grid, the primary control node mayopen a pair of listening sockets, for example. A socket may be used toaccept work requests from clients, and the second socket may be used toaccept connections from other grid nodes. The primary control node maybe provided with a list of other nodes (e.g., other machines, computers,servers) that will participate in the grid, and the role that each nodewill fill in the grid. Upon startup of the primary control node (e.g.,the first node on the grid), the primary control node may use a networkprotocol to start the server process on every other node in the grid.Command line parameters, for example, may inform each node of one ormore pieces of information, such as: the role that the node will have inthe grid, the host name of the primary control node, the port number onwhich the primary control node is accepting connections from peer nodes,among others. The information may also be provided in a configurationfile, transmitted over a secure shell tunnel, recovered from aconfiguration server, among others. While the other machines in the gridmay not initially know about the configuration of the grid, thatinformation may also be sent to each other node by the primary controlnode. Updates of the grid information may also be subsequently sent tothose nodes.

For any control node other than the primary control node added to thegrid, the control node may open three sockets. The first socket mayaccept work requests from clients, the second socket may acceptconnections from other grid members, and the third socket may connect(e.g., permanently) to the primary control node. When a control node(e.g., primary control node) receives a connection from another controlnode, it first checks to see if the peer node is in the list ofconfigured nodes in the grid. If it is not on the list, the control nodemay clear the connection. If it is on the list, it may then attempt toauthenticate the connection. If authentication is successful, theauthenticating node may transmit information to its peer, such as theport number on which a node is listening for connections, the host nameof the node, information about how to authenticate the node, among otherinformation. When a node, such as the new control node, receivesinformation about another active node, it will check to see if italready has a connection to that other node. If it does not have aconnection to that node, it may then establish a connection to thatcontrol node.

Any worker node added to the grid may establish a connection to theprimary control node and any other control nodes on the grid. Afterestablishing the connection, it may authenticate itself to the grid(e.g., any control nodes, including both primary and backup, or a serveror user controlling the grid). After successful authentication, theworker node may accept configuration information from the control node.

When a node joins a communications grid (e.g., when the node is poweredon or connected to an existing node on the grid or both), the node isassigned (e.g., by an operating system of the grid) a universally uniqueidentifier (UUID). This unique identifier may help other nodes andexternal entities (devices, users, etc.) to identify the node anddistinguish it from other nodes. When a node is connected to the grid,the node may share its unique identifier with the other nodes in thegrid. Since each node may share its unique identifier, each node mayknow the unique identifier of every other node on the grid. Uniqueidentifiers may also designate a hierarchy of each of the nodes (e.g.,backup control nodes) within the grid. For example, the uniqueidentifiers of each of the backup control nodes may be stored in a listof backup control nodes to indicate an order in which the backup controlnodes will take over for a failed primary control node to become a newprimary control node. However, a hierarchy of nodes may also bedetermined using methods other than using the unique identifiers of thenodes. For example, the hierarchy may be predetermined, or may beassigned based on other predetermined factors.

The grid may add new machines at any time (e.g., initiated from anycontrol node). Upon adding a new node to the grid, the control node mayfirst add the new node to its table of grid nodes. The control node mayalso then notify every other control node about the new node. The nodesreceiving the notification may acknowledge that they have updated theirconfiguration information.

Primary control node 402 may, for example, transmit one or morecommunications to backup control nodes 404 and 406 (and, for example, toother control or worker nodes within the communications grid). Suchcommunications may sent periodically, at fixed time intervals, betweenknown fixed stages of the project's execution, among other protocols.The communications transmitted by primary control node 402 may be ofvaried types and may include a variety of types of information. Forexample, primary control node 402 may transmit snapshots (e.g., statusinformation) of the communications grid so that backup control node 404always has a recent snapshot of the communications grid. The snapshot orgrid status may include, for example, the structure of the grid(including, for example, the worker nodes in the grid, uniqueidentifiers of the nodes, or their relationships with the primarycontrol node) and the status of a project (including, for example, thestatus of each worker node's portion of the project). The snapshot mayalso include analysis or results received from worker nodes in thecommunications grid. The backup control nodes may receive and store thebackup data received from the primary control node. The backup controlnodes may transmit a request for such a snapshot (or other information)from the primary control node, or the primary control node may send suchinformation periodically to the backup control nodes.

As noted, the backup data may allow the backup control node to take overas primary control node if the primary control node fails withoutrequiring the grid to start the project over from scratch. If theprimary control node fails, the backup control node that will take overas primary control node may retrieve the most recent version of thesnapshot received from the primary control node and use the snapshot tocontinue the project from the stage of the project indicated by thebackup data. This may prevent failure of the project as a whole.

A backup control node may use various methods to determine that theprimary control node has failed. In one example of such a method, theprimary control node may transmit (e.g., periodically) a communicationto the backup control node that indicates that the primary control nodeis working and has not failed, such as a heartbeat communication. Thebackup control node may determine that the primary control node hasfailed if the backup control node has not received a heartbeatcommunication for a certain predetermined period of time. Alternatively,a backup control node may also receive a communication from the primarycontrol node itself (before it failed) or from a worker node that theprimary control node has failed, for example because the primary controlnode has failed to communicate with the worker node.

Different methods may be performed to determine which backup controlnode of a set of backup control nodes (e.g., backup control nodes 404and 406) will take over for failed primary control node 402 and becomethe new primary control node. For example, the new primary control nodemay be chosen based on a ranking or “hierarchy” of backup control nodesbased on their unique identifiers. In an alternative embodiment, abackup control node may be assigned to be the new primary control nodeby another device in the communications grid or from an external device(e.g., a system infrastructure or an end user, such as a server orcomputer, controlling the communications grid). In another alternativeembodiment, the backup control node that takes over as the new primarycontrol node may be designated based on bandwidth or other statisticsabout the communications grid.

A worker node within the communications grid may also fail. If a workernode fails, work being performed by the failed worker node may beredistributed amongst the operational worker nodes. In an alternativeembodiment, the primary control node may transmit a communication toeach of the operable worker nodes still on the communications grid thateach of the worker nodes should purposefully fail also. After each ofthe worker nodes fail, they may each retrieve their most recent savedcheckpoint of their status and re-start the project from that checkpointto minimize lost progress on the project being executed.

FIG. 5 illustrates a flow chart showing an example process 500 foradjusting a communications grid or a work project in a communicationsgrid after a failure of a node, according to embodiments of the presenttechnology. The process may include, for example, receiving grid statusinformation including a project status of a portion of a project beingexecuted by a node in the communications grid, as described in operation502. For example, a control node (e.g., a backup control node connectedto a primary control node and a worker node on a communications grid)may receive grid status information, where the grid status informationincludes a project status of the primary control node or a projectstatus of the worker node. The project status of the primary controlnode and the project status of the worker node may include a status ofone or more portions of a project being executed by the primary andworker nodes in the communications grid. The process may also includestoring the grid status information, as described in operation 504. Forexample, a control node (e.g., a backup control node) may store thereceived grid status information locally within the control node.Alternatively, the grid status information may be sent to another devicefor storage where the control node may have access to the information.

The process may also include receiving a failure communicationcorresponding to a node in the communications grid in operation 506. Forexample, a node may receive a failure communication including anindication that the primary control node has failed, prompting a backupcontrol node to take over for the primary control node. In analternative embodiment, a node may receive a failure that a worker nodehas failed, prompting a control node to reassign the work beingperformed by the worker node. The process may also include reassigning anode or a portion of the project being executed by the failed node, asdescribed in operation 508. For example, a control node may designatethe backup control node as a new primary control node based on thefailure communication upon receiving the failure communication. If thefailed node is a worker node, a control node may identify a projectstatus of the failed worker node using the snapshot of thecommunications grid, where the project status of the failed worker nodeincludes a status of a portion of the project being executed by thefailed worker node at the failure time.

The process may also include receiving updated grid status informationbased on the reassignment, as described in operation 510, andtransmitting a set of instructions based on the updated grid statusinformation to one or more nodes in the communications grid, asdescribed in operation 512. The updated grid status information mayinclude an updated project status of the primary control node or anupdated project status of the worker node. The updated information maybe transmitted to the other nodes in the grid to update their stalestored information.

FIG. 6 illustrates a portion of a communications grid computing system600 including a control node and a worker node, according to embodimentsof the present technology. Communications grid 600 computing systemincludes one control node (control node 602) and one worker node (workernode 610) for purposes of illustration, but may include more workerand/or control nodes. The control node 602 is communicatively connectedto worker node 610 via communication path 650. Therefore, control node602 may transmit information (e.g., related to the communications gridor notifications), to and receive information from worker node 610 viapath 650.

Similar to in FIG. 4, communications grid computing system (or just“communications grid”) 600 includes data processing nodes (control node602 and worker node 610). Nodes 602 and 610 include multi-core dataprocessors. Each node 602 and 610 includes a grid-enabled softwarecomponent (GESC) 620 that executes on the data processor associated withthat node and interfaces with buffer memory 622 also associated withthat node. Each node 602 and 610 includes a database management software(DBMS) 628 that executes on a database server (not shown) at controlnode 602 and on a database server (not shown) at worker node 610.

Each node also includes a data store 624. Data stores 624, similar tonetwork-attached data stores 110 in FIG. 1 and data stores 235 in FIG.2, are used to store data to be processed by the nodes in the computingenvironment. Data stores 624 may also store any intermediate or finaldata generated by the computing system after being processed, forexample in non-volatile memory. However in certain embodiments, theconfiguration of the grid computing environment allows its operations tobe performed such that intermediate and final data results can be storedsolely in volatile memory (e.g., RAM), without a requirement thatintermediate or final data results be stored to non-volatile types ofmemory. Storing such data in volatile memory may be useful in certainsituations, such as when the grid receives queries (e.g., ad hoc) from aclient and when responses, which are generated by processing largeamounts of data, need to be generated quickly or on-the-fly. In such asituation, the grid may be configured to retain the data within memoryso that responses can be generated at different levels of detail and sothat a client may interactively query against this information.

Each node also includes a user-defined function (UDF) 626. The UDFprovides a mechanism for the DBMS 628 to transfer data to or receivedata from the database stored in the data stores 624 that are managed bythe DBMS. For example, UDF 626 can be invoked by the DBMS to providedata to the GESC for processing. The UDF 626 may establish a socketconnection (not shown) with the GESC to transfer the data.Alternatively, the UDF 626 can transfer data to the GESC by writing datato shared memory accessible by both the UDF and the GESC.

The GESC 620 at the nodes 602 and 620 may be connected via a network,such as network 108 shown in FIG. 1. Therefore, nodes 602 and 620 cancommunicate with each other via the network using a predeterminedcommunication protocol such as, for example, the Message PassingInterface (MPI). Each GESC 620 can engage in point-to-pointcommunication with the GESC at another node or in collectivecommunication with multiple GESCs via the network. The GESC 620 at eachnode may contain identical (or nearly identical) software instructions.Each node may be capable of operating as either a control node or aworker node. The GESC at the control node 602 can communicate, over acommunication path 652, with a client deice 630. More specifically,control node 602 may communicate with client application 632 hosted bythe client device 630 to receive queries and to respond to those queriesafter processing large amounts of data.

DBMS 628 may control the creation, maintenance, and use of database ordata structure (not shown) within a nodes 602 or 610. The database mayorganize data stored in data stores 624. The DBMS 628 at control node602 may accept requests for data and transfer the appropriate data forthe request. With such a process, collections of data may be distributedacross multiple physical locations. In this example, each node 602 and610 stores a portion of the total data managed by the management systemin its associated data store 624.

Furthermore, the DBMS may be responsible for protecting against dataloss using replication techniques. Replication includes providing abackup copy of data stored on one node on one or more other nodes.Therefore, if one node fails, the data from the failed node can berecovered from a replicated copy residing at another node. However, asdescribed herein with respect to FIG. 4, data or status information foreach node in the communications grid may also be shared with each nodeon the grid.

FIG. 7 illustrates a flow chart showing an example method 700 forexecuting a project within a grid computing system, according toembodiments of the present technology. As described with respect to FIG.6, the GESC at the control node may transmit data with a client device(e.g., client device 630) to receive queries for executing a project andto respond to those queries after large amounts of data have beenprocessed. The query may be transmitted to the control node, where thequery may include a request for executing a project, as described inoperation 702. The query can contain instructions on the type of dataanalysis to be performed in the project and whether the project shouldbe executed using the grid-based computing environment, as shown inoperation 704.

To initiate the project, the control node may determine if the queryrequests use of the grid-based computing environment to execute theproject. If the determination is no, then the control node initiatesexecution of the project in a solo environment (e.g., at the controlnode), as described in operation 710. If the determination is yes, thecontrol node may initiate execution of the project in the grid-basedcomputing environment, as described in operation 706. In such asituation, the request may include a requested configuration of thegrid. For example, the request may include a number of control nodes anda number of worker nodes to be used in the grid when executing theproject. After the project has been completed, the control node maytransmit results of the analysis yielded by the grid, as described inoperation 708. Whether the project is executed in a solo or grid-basedenvironment, the control node provides the results of the project, asdescribed in operation 712.

As noted with respect to FIG. 2, the computing environments describedherein may collect data (e.g., as received from network devices, such assensors, such as network devices 204-209 in FIG. 2, and client devicesor other sources) to be processed as part of a data analytics project,and data may be received in real time as part of a streaming analyticsenvironment (e.g., ESP). Data may be collected using a variety ofsources as communicated via different kinds of networks or locally, suchas on a real-time streaming basis. For example, network devices mayreceive data periodically from network device sensors as the sensorscontinuously sense, monitor and track changes in their environments.More specifically, an increasing number of distributed applicationsdevelop or produce continuously flowing data from distributed sources byapplying queries to the data before distributing the data togeographically distributed recipients. An event stream processing engine(ESPE) may continuously apply the queries to the data as it is receivedand determines which entities should receive the data. Client or otherdevices may also subscribe to the ESPE or other devices processing ESPdata so that they can receive data after processing, based on forexample the entities determined by the processing engine. For example,client devices 230 in FIG. 2 may subscribe to the ESPE in computingenvironment 214. In another example, event subscription devices 1024a-c, described further with respect to FIG. 10, may also subscribe tothe ESPE. The ESPE may determine or define how input data or eventstreams from network devices or other publishers (e.g., network devices204-209 in FIG. 2) are transformed into meaningful output data to beconsumed by subscribers, such as for example client devices 230 in FIG.2.

FIG. 8 illustrates a block diagram including components of an EventStream Processing Engine (ESPE), according to embodiments of the presenttechnology. ESPE 800 may include one or more projects 802. A project maybe described as a second-level container in an engine model managed byESPE 800 where a thread pool size for the project may be defined by auser. Each project of the one or more projects 802 may include one ormore continuous queries 804 that contain data flows, which are datatransformations of incoming event streams. The one or more continuousqueries 804 may include one or more source windows 806 and one or morederived windows 808.

The ESPE may receive streaming data over a period of time related tocertain events, such as events or other data sensed by one or morenetwork devices. The ESPE may perform operations associated withprocessing data created by the one or more devices. For example, theESPE may receive data from the one or more network devices 204-209 shownin FIG. 2. As noted, the network devices may include sensors that sensedifferent aspects of their environments, and may collect data over timebased on those sensed observations. For example, the ESPE may beimplemented within one or more of machines 220 and 240 shown in FIG. 2.The ESPE may be implemented within such a machine by an ESP application.An ESP application may embed an ESPE with its own dedicated thread poolor pools into its application space where the main application threadcan do application-specific work and the ESPE processes event streams atleast by creating an instance of a model into processing objects.

The engine container is the top-level container in a model that managesthe resources of the one or more projects 802. In an illustrativeembodiment, for example, there may be only one ESPE 800 for eachinstance of the ESP application, and ESPE 800 may have a unique enginename. Additionally, the one or more projects 802 may each have uniqueproject names, and each query may have a unique continuous query nameand begin with a uniquely named source window of the one or more sourcewindows 806. ESPE 800 may or may not be persistent.

Continuous query modeling involves defining directed graphs of windowsfor event stream manipulation and transformation. A window in thecontext of event stream manipulation and transformation is a processingnode in an event stream processing model. A window in a continuous querycan perform aggregations, computations, pattern-matching, and otheroperations on data flowing through the window. A continuous query may bedescribed as a directed graph of source, relational, pattern matching,and procedural windows. The one or more source windows 806 and the oneor more derived windows 808 represent continuously executing queriesthat generate updates to a query result set as new event blocks streamthrough ESPE 800. A directed graph, for example, is a set of nodesconnected by edges, where the edges have a direction associated withthem.

An event object may be described as a packet of data accessible as acollection of fields, with at least one of the fields defined as a keyor unique identifier (ID). The event object may be created using avariety of formats including binary, alphanumeric, XML, etc. Each eventobject may include one or more fields designated as a primary identifier(ID) for the event so ESPE 800 can support operation codes (opcodes) forevents including insert, update, upsert, and delete. Upsert opcodesupdate the event if the key field already exists; otherwise, the eventis inserted. For illustration, an event object may be a packed binaryrepresentation of a set of field values and include both metadata andfield data associated with an event. The metadata may include an opcodeindicating if the event represents an insert, update, delete, or upsert,a set of flags indicating if the event is a normal, partial-update, or aretention generated event from retention policy management, and a set ofmicrosecond timestamps that can be used for latency measurements.

An event block object may be described as a grouping or package of eventobjects. An event stream may be described as a flow of event blockobjects. A continuous query of the one or more continuous queries 804transforms a source event stream made up of streaming event blockobjects published into ESPE 800 into one or more output event streamsusing the one or more source windows 806 and the one or more derivedwindows 808. A continuous query can also be thought of as data flowmodeling.

The one or more source windows 806 are at the top of the directed graphand have no windows feeding into them. Event streams are published intothe one or more source windows 806, and from there, the event streamsmay be directed to the next set of connected windows as defined by thedirected graph. The one or more derived windows 808 are all instantiatedwindows that are not source windows and that have other windowsstreaming events into them. The one or more derived windows 808 mayperform computations or transformations on the incoming event streams.The one or more derived windows 808 transform event streams based on thewindow type (that is operators such as join, filter, compute, aggregate,copy, pattern match, procedural, union, etc.) and window settings. Asevent streams are published into ESPE 800, they are continuouslyqueried, and the resulting sets of derived windows in these queries arecontinuously updated.

FIG. 9 illustrates a flow chart showing an example process includingoperations performed by an event stream processing engine, according tosome embodiments of the present technology. As noted, the ESPE 800 (oran associated ESP application) defines how input event streams aretransformed into meaningful output event streams. More specifically, theESP application may define how input event streams from publishers(e.g., network devices providing sensed data) are transformed intomeaningful output event streams consumed by subscribers (e.g., a dataanalytics project being executed by a machine or set of machines).

Within the application, a user may interact with one or more userinterface windows presented to the user in a display under control ofthe ESPE independently or through a browser application in an orderselectable by the user. For example, a user may execute an ESPapplication, which causes presentation of a first user interface window,which may include a plurality of menus and selectors such as drop downmenus, buttons, text boxes, hyperlinks, etc. associated with the ESPapplication as understood by a person of skill in the art. As furtherunderstood by a person of skill in the art, various operations may beperformed in parallel, for example, using a plurality of threads.

At operation 900, an ESP application may define and start an ESPE,thereby instantiating an ESPE at a device, such as machine 220 and/or240. In an operation 902, the engine container is created. Forillustration, ESPE 800 may be instantiated using a function call thatspecifies the engine container as a manager for the model.

In an operation 904, the one or more continuous queries 804 areinstantiated by ESPE 800 as a model. The one or more continuous queries804 may be instantiated with a dedicated thread pool or pools thatgenerate updates as new events stream through ESPE 800. Forillustration, the one or more continuous queries 804 may be created tomodel business processing logic within ESPE 800, to predict eventswithin ESPE 800, to model a physical system within ESPE 800, to predictthe physical system state within ESPE 800, etc. For example, as noted,ESPE 800 may be used to support sensor data monitoring and management(e.g., sensing may include force, torque, load, strain, position,temperature, air pressure, fluid flow, chemical properties, resistance,electromagnetic fields, radiation, irradiance, proximity, acoustics,moisture, distance, speed, vibrations, acceleration, electricalpotential, or electrical current, etc.).

ESPE 800 may analyze and process events in motion or “event streams.”Instead of storing data and running queries against the stored data,ESPE 800 may store queries and stream data through them to allowcontinuous analysis of data as it is received. The one or more sourcewindows 806 and the one or more derived windows 808 may be created basedon the relational, pattern matching, and procedural algorithms thattransform the input event streams into the output event streams tomodel, simulate, score, test, predict, etc. based on the continuousquery model defined and application to the streamed data.

In an operation 906, a publish/subscribe (pub/sub) capability isinitialized for ESPE 800. In an illustrative embodiment, a pub/subcapability is initialized for each project of the one or more projects802. To initialize and enable pub/sub capability for ESPE 800, a portnumber may be provided. Pub/sub clients can use a host name of an ESPdevice running the ESPE and the port number to establish pub/subconnections to ESPE 800.

FIG. 10 illustrates an ESP system 1000 interfacing between publishingdevice 1022 and event subscribing devices 1024 a-c, according toembodiments of the present technology. ESP system 1000 may include ESPdevice or subsystem 851, event publishing device 1022, an eventsubscribing device A 1024 a, an event subscribing device B 1024 b, andan event subscribing device C 1024 c. Input event streams are output toESP device 851 by publishing device 1022. In alternative embodiments,the input event streams may be created by a plurality of publishingdevices. The plurality of publishing devices further may publish eventstreams to other ESP devices. The one or more continuous queriesinstantiated by ESPE 800 may analyze and process the input event streamsto form output event streams output to event subscribing device A 1024a, event subscribing device B 1024 b, and event subscribing device C1024 c. ESP system 1000 may include a greater or a fewer number of eventsubscribing devices of event subscribing devices.

Publish-subscribe is a message-oriented interaction paradigm based onindirect addressing. Processed data recipients specify their interest inreceiving information from ESPE 800 by subscribing to specific classesof events, while information sources publish events to ESPE 800 withoutdirectly addressing the receiving parties. ESPE 800 coordinates theinteractions and processes the data. In some cases, the data sourcereceives confirmation that the published information has been receivedby a data recipient.

A publish/subscribe API may be described as a library that enables anevent publisher, such as publishing device 1022, to publish eventstreams into ESPE 800 or an event subscriber, such as event subscribingdevice A 1024 a, event subscribing device B 1024 b, and eventsubscribing device C 1024 c, to subscribe to event streams from ESPE800. For illustration, one or more publish/subscribe APIs may bedefined. Using the publish/subscribe API, an event publishingapplication may publish event streams into a running event streamprocessor project source window of ESPE 800, and the event subscriptionapplication may subscribe to an event stream processor project sourcewindow of ESPE 800.

The publish/subscribe API provides cross-platform connectivity andendianness compatibility between ESP application and other networkedapplications, such as event publishing applications instantiated atpublishing device 1022, and event subscription applications instantiatedat one or more of event subscribing device A 1024 a, event subscribingdevice B 1024 b, and event subscribing device C 1024 c.

Referring back to FIG. 9, operation 906 initializes thepublish/subscribe capability of ESPE 800. In an operation 908, the oneor more projects 802 are started. The one or more started projects mayrun in the background on an ESP device. In an operation 910, an eventblock object is received from one or more computing device of the eventpublishing device 1022.

ESP subsystem 800 may include a publishing client 1002, ESPE 800, asubscribing client A 1004, a subscribing client B 1006, and asubscribing client C 1008. Publishing client 1002 may be started by anevent publishing application executing at publishing device 1022 usingthe publish/subscribe API. Subscribing client A 1004 may be started byan event subscription application A, executing at event subscribingdevice A 1024 a using the publish/subscribe API. Subscribing client B1006 may be started by an event subscription application B executing atevent subscribing device B 1024 b using the publish/subscribe API.Subscribing client C 1008 may be started by an event subscriptionapplication C executing at event subscribing device C 1024 c using thepublish/subscribe API.

An event block object containing one or more event objects is injectedinto a source window of the one or more source windows 806 from aninstance of an event publishing application on event publishing device1022. The event block object may generated, for example, by the eventpublishing application and may be received by publishing client 1002. Aunique ID may be maintained as the event block object is passed betweenthe one or more source windows 806 and/or the one or more derivedwindows 808 of ESPE 800, and to subscribing client A 1004, subscribingclient B 1006, and subscribing client C 1008 and to event subscriptiondevice A 1024 a, event subscription device B 1024 b, and eventsubscription device C 1024 c. Publishing client 1002 may furthergenerate and include a unique embedded transaction ID in the event blockobject as the event block object is processed by a continuous query, aswell as the unique ID that publishing device 1022 assigned to the eventblock object.

In an operation 912, the event block object is processed through the oneor more continuous queries 804. In an operation 914, the processed eventblock object is output to one or more computing devices of the eventsubscribing devices 1024 a-c. For example, subscribing client A 1004,subscribing client B 1006, and subscribing client C 1008 may send thereceived event block object to event subscription device A 1024 a, eventsubscription device B 1024 b, and event subscription device C 1024 c,respectively.

ESPE 800 maintains the event block containership aspect of the receivedevent blocks from when the event block is published into a source windowand works its way through the directed graph defined by the one or morecontinuous queries 804 with the various event translations before beingoutput to subscribers. Subscribers can correlate a group of subscribedevents back to a group of published events by comparing the unique ID ofthe event block object that a publisher, such as publishing device 1022,attached to the event block object with the event block ID received bythe subscriber.

In an operation 916, a determination is made concerning whether or notprocessing is stopped. If processing is not stopped, processingcontinues in operation 910 to continue receiving the one or more eventstreams containing event block objects from the, for example, one ormore network devices. If processing is stopped, processing continues inan operation 918. In operation 918, the started projects are stopped. Inoperation 920, the ESPE is shutdown.

As noted, in some embodiments, big data is processed for an analyticsproject after the data is received and stored. In other embodiments,distributed applications process continuously flowing data in real-timefrom distributed sources by applying queries to the data beforedistributing the data to geographically distributed recipients. Asnoted, an event stream processing engine (ESPE) may continuously applythe queries to the data as it is received and determines which entitiesreceive the processed data. This allows for large amounts of data beingreceived and/or collected in a variety of environments to be processedand distributed in real time. For example, as shown with respect to FIG.2, data may be collected from network devices that may include deviceswithin the internet of things, such as devices within a home automationnetwork. However, such data may be collected from a variety of differentresources in a variety of different environments. In any such situation,embodiments of the present technology allow for real-time processing ofsuch data.

Aspects of the current disclosure provide technical solutions totechnical problems, such as computing problems that arise when an ESPdevice fails which results in a complete service interruption andpotentially significant data loss. The data loss can be catastrophicwhen the streamed data is supporting mission critical operations such asthose in support of an ongoing manufacturing or drilling operation. Anembodiment of an ESP system achieves a rapid and seamless failover ofESPE running at the plurality of ESP devices without serviceinterruption or data loss, thus significantly improving the reliabilityof an operational system that relies on the live or real-time processingof the data streams. The event publishing systems, the event subscribingsystems, and each ESPE not executing at a failed ESP device are notaware of or effected by the failed ESP device. The ESP system mayinclude thousands of event publishing systems and event subscribingsystems. The ESP system keeps the failover logic and awareness withinthe boundaries of out-messaging network connector and out-messagingnetwork device.

In one example embodiment, a system is provided to support a failoverwhen event stream processing (ESP) event blocks. The system includes,but is not limited to, an out-messaging network device and a computingdevice. The computing device includes, but is not limited to, aprocessor and a computer-readable medium operably coupled to theprocessor. The processor is configured to execute an ESP engine (ESPE).The computer-readable medium has instructions stored thereon that, whenexecuted by the processor, cause the computing device to support thefailover. An event block object is received from the ESPE that includesa unique identifier. A first status of the computing device as active orstandby is determined. When the first status is active, a second statusof the computing device as newly active or not newly active isdetermined. Newly active is determined when the computing device isswitched from a standby status to an active status. When the secondstatus is newly active, a last published event block object identifierthat uniquely identifies a last published event block object isdetermined. A next event block object is selected from a non-transitorycomputer-readable medium accessible by the computing device. The nextevent block object has an event block object identifier that is greaterthan the determined last published event block object identifier. Theselected next event block object is published to an out-messagingnetwork device. When the second status of the computing device is notnewly active, the received event block object is published to theout-messaging network device. When the first status of the computingdevice is standby, the received event block object is stored in thenon-transitory computer-readable medium.

FIG. 11 is a flow chart of an example of a process for generating andusing a machine-learning model according to some aspects. Machinelearning is a branch of artificial intelligence that relates tomathematical models that can learn from, categorize, and makepredictions about data. Such mathematical models, which can be referredto as machine-learning models, can classify input data among two or moreclasses; cluster input data among two or more groups; predict a resultbased on input data; identify patterns or trends in input data; identifya distribution of input data in a space; or any combination of these.Examples of machine-learning models can include (i) neural networks;(ii) decision trees, such as classification trees and regression trees;(iii) classifiers, such as Naïve bias classifiers, logistic regressionclassifiers, ridge regression classifiers, random forest classifiers,least absolute shrinkage and selector (LASSO) classifiers, and supportvector machines; (iv) clusterers, such as k-means clusterers, mean-shiftclusterers, and spectral clusterers; (v) factorizers, such asfactorization machines, principal component analyzers and kernelprincipal component analyzers; and (vi) ensembles or other combinationsof machine-learning models. In some examples, neural networks caninclude deep neural networks, feed-forward neural networks, recurrentneural networks, convolutional neural networks, radial basis function(RBF) neural networks, echo state neural networks, long short-termmemory neural networks, bi-directional recurrent neural networks, gatedneural networks, hierarchical recurrent neural networks, stochasticneural networks, modular neural networks, spiking neural networks,dynamic neural networks, cascading neural networks, neuro-fuzzy neuralnetworks, or any combination of these.

Different machine-learning models may be used interchangeably to performa task. Examples of tasks that can be performed at least partially usingmachine-learning models include various types of scoring;bioinformatics; cheminformatics; software engineering; fraud detection;customer segmentation; generating online recommendations; adaptivewebsites; determining customer lifetime value; search engines; placingadvertisements in real time or near real time; classifying DNAsequences; affective computing; performing natural language processingand understanding; object recognition and computer vision; roboticlocomotion; playing games; optimization and metaheuristics; detectingnetwork intrusions; medical diagnosis and monitoring; or predicting whenan asset, such as a machine, will need maintenance.

Any number and combination of tools can be used to createmachine-learning models. Examples of tools for creating and managingmachine-learning models can include SAS® Enterprise Miner, SAS® RapidPredictive Modeler, and SAS® Model Manager, SAS Cloud Analytic Services(CAS)®, SAS Viya® of all which are by SAS Institute Inc. of Cary, N.C.

Machine-learning models can be constructed through an at least partiallyautomated (e.g., with little or no human involvement) process calledtraining. During training, input data can be iteratively supplied to amachine-learning model to enable the machine-learning model to identifypatterns related to the input data or to identify relationships betweenthe input data and output data. With training, the machine-learningmodel can be transformed from an untrained state to a trained state.Input data can be split into one or more training sets and one or morevalidation sets, and the training process may be repeated multipletimes. The splitting may follow a k-fold cross-validation rule, aleave-one-out-rule, a leave-p-out rule, or a holdout rule. An overviewof training and using a machine-learning model is described below withrespect to the flow chart of FIG. 11.

In block 1104, training data is received. In some examples, the trainingdata is received from a remote database or a local database, constructedfrom various subsets of data, or input by a user. The training data canbe used in its raw form for training a machine-learning model orpre-processed into another form, which can then be used for training themachine-learning model. For example, the raw form of the training datacan be smoothed, truncated, aggregated, clustered, or otherwisemanipulated into another form, which can then be used for training themachine-learning model.

In block 1106, a machine-learning model is trained using the trainingdata. The machine-learning model can be trained in a supervised,unsupervised, or semi-supervised manner In supervised training, eachinput in the training data is correlated to a desired output. Thisdesired output may be a scalar, a vector, or a different type of datastructure such as text or an image. This may enable the machine-learningmodel to learn a mapping between the inputs and desired outputs. Inunsupervised training, the training data includes inputs, but notdesired outputs, so that the machine-learning model has to findstructure in the inputs on its own. In semi-supervised training, onlysome of the inputs in the training data are correlated to desiredoutputs.

In block 1108, the machine-learning model is evaluated. For example, anevaluation dataset can be obtained, for example, via user input or froma database. The evaluation dataset can include inputs correlated todesired outputs. The inputs can be provided to the machine-learningmodel and the outputs from the machine-learning model can be compared tothe desired outputs. If the outputs from the machine-learning modelclosely correspond with the desired outputs, the machine-learning modelmay have a high degree of accuracy. For example, if 90% or more of theoutputs from the machine-learning model are the same as the desiredoutputs in the evaluation dataset, the machine-learning model may have ahigh degree of accuracy. Otherwise, the machine-learning model may havea low degree of accuracy. The 90% number is an example only. A realisticand desirable accuracy percentage is dependent on the problem and thedata.

In some examples, if the machine-learning model has an inadequate degreeof accuracy for a particular task, the process can return to block 1106,where the machine-learning model can be further trained using additionaltraining data or otherwise modified to improve accuracy. If themachine-learning model has an adequate degree of accuracy for theparticular task, the process can continue to block 1110.

In block 1110, new data is received. In some examples, the new data isreceived from a remote database or a local database, constructed fromvarious subsets of data, or input by a user. The new data may be unknownto the machine-learning model. For example, the machine-learning modelmay not have previously processed or analyzed the new data.

In block 1112, the trained machine-learning model is used to analyze thenew data and provide a result. For example, the new data can be providedas input to the trained machine-learning model. The trainedmachine-learning model can analyze the new data and provide a resultthat includes a classification of the new data into a particular class,a clustering of the new data into a particular group, a prediction basedon the new data, or any combination of these.

In block 1114, the result is post-processed. For example, the result canbe added to, multiplied with, or otherwise combined with other data aspart of a job. As another example, the result can be transformed from afirst format, such as a time series format, into another format, such asa count series format. Any number and combination of operations can beperformed on the result during post-processing.

A more specific example of a machine-learning model is the neuralnetwork 1200 shown in FIG. 12. The neural network 1200 is represented asmultiple layers of interconnected neurons, such as neuron 1208, that canexchange data between one another. The layers include an input layer1202 for receiving input data, a hidden layer 1204, and an output layer1206 for providing a result. The hidden layer 1204 is referred to ashidden because it may not be directly observable or have its inputdirectly accessible during the normal functioning of the neural network1200. Although the neural network 1200 is shown as having a specificnumber of layers and neurons for exemplary purposes, the neural network1200 can have any number and combination of layers, and each layer canhave any number and combination of neurons.

The neurons and connections between the neurons can have numericweights, which can be tuned during training. For example, training datacan be provided to the input layer 1202 of the neural network 1200, andthe neural network 1200 can use the training data to tune one or morenumeric weights of the neural network 1200. In some examples, the neuralnetwork 1200 can be trained using backpropagation. Backpropagation caninclude determining a gradient of a particular numeric weight based on adifference between an actual output of the neural network 1200 and adesired output of the neural network 1200. Based on the gradient, one ormore numeric weights of the neural network 1200 can be updated to reducethe difference, thereby increasing the accuracy of the neural network1200. This process can be repeated multiple times to train the neuralnetwork 1200. For example, this process can be repeated hundreds orthousands of times to train the neural network 1200.

In some examples, the neural network 1200 is a feed-forward neuralnetwork. In a feed-forward neural network, every neuron only propagatesan output value to a subsequent layer of the neural network 1200. Forexample, data may only move one direction (forward) from one neuron tothe next neuron in a feed-forward neural network.

In other examples, the neural network 1200 is a recurrent neuralnetwork. A recurrent neural network can include one or more feedbackloops, allowing data to propagate in both forward and backward throughthe neural network 1200. This can allow for information to persistwithin the recurrent neural network. For example, a recurrent neuralnetwork can determine an output based at least partially on informationthat the recurrent neural network has seen before, giving the recurrentneural network the ability to use previous input to inform the output.

In some examples, the neural network 1200 operates by receiving a vectorof numbers from one layer; transforming the vector of numbers into a newvector of numbers using a matrix of numeric weights, a nonlinearity, orboth; and providing the new vector of numbers to a subsequent layer ofthe neural network 1200. Each subsequent layer of the neural network1200 can repeat this process until the neural network 1200 outputs afinal result at the output layer 1206. For example, the neural network1200 can receive a vector of numbers as an input at the input layer1202. The neural network 1200 can multiply the vector of numbers by amatrix of numeric weights to determine a weighted vector. The matrix ofnumeric weights can be tuned during the training of the neural network1200. The neural network 1200 can transform the weighted vector using anonlinearity, such as a sigmoid tangent or the hyperbolic tangent. Insome examples, the nonlinearity can include a rectified linear unit,which can be expressed using the equation y=max(x, 0) where y is theoutput and x is an input value from the weighted vector. The transformedoutput can be supplied to a subsequent layer, such as the hidden layer1204, of the neural network 1200. The subsequent layer of the neuralnetwork 1200 can receive the transformed output, multiply thetransformed output by a matrix of numeric weights and a nonlinearity,and provide the result to yet another layer of the neural network 1200.This process continues until the neural network 1200 outputs a finalresult at the output layer 1206.

Other examples of the present disclosure may include any number andcombination of machine-learning models having any number and combinationof characteristics. The machine-learning model(s) can be trained in asupervised, semi-supervised, or unsupervised manner, or any combinationof these. The machine-learning model(s) can be implemented using asingle computing device or multiple computing devices, such as thecommunications grid computing system 400 discussed above.

Implementing some examples of the present disclosure at least in part byusing machine-learning models can reduce the total number of processingiterations, time, memory, electrical power, or any combination of theseconsumed by a computing device when analyzing data. For example, aneural network may more readily identify patterns in data than otherapproaches. This may enable the neural network to analyze the data usingfewer processing cycles and less memory than other approaches, whileobtaining a similar or greater level of accuracy.

Some machine-learning approaches may be more efficiently and speedilyexecuted and processed with machine-learning specific processors (e.g.,not a generic CPU). Such processors may also provide an energy savingswhen compared to generic CPUs. For example, some of these processors caninclude a graphical processing unit (GPU), an application-specificintegrated circuit (ASIC), a field-programmable gate array (FPGA), anartificial intelligence (AI) accelerator, a neural computing core, aneural computing engine, a neural processing unit, a purpose-built chiparchitecture for deep learning, and/or some other machine-learningspecific processor that implements a machine learning approach or one ormore neural networks using semiconductor (e.g., silicon (Si), galliumarsenide(GaAs)) devices. These processors may also be employed inheterogeneous computing architectures with a number of and a variety ofdifferent types of cores, engines, nodes, and/or layers to achievevarious energy efficiencies, processing speed improvements, datacommunication speed improvements, and/or data efficiency targets andimprovements throughout various parts of the system when compared to ahomogeneous computing architecture that employs CPUs for general purposecomputing.

FIG. 13A is a block diagram of an example embodiment of a distributedprocessing system 2000 incorporating one or more source devices 2100,one or more reviewing devices 2800, one or more federated devices 2500that may form a federated device grid 2005, and/or one or more storagedevices 2600 that may form a storage device grid 2006. FIG. 13Billustrates exchanges, through a network 2999, of communications amongthe devices 2100, 2500, 2600 and/or 2800 associated with the controlledstorage of, access to and/or performance of job flows of analysesassociated with various objects within one or more federated areas 2566.FIG. 13C illustrates embodiments in which such exchanges are performedin response to requests from the devices 2100 and/or 2800. FIG. 13Dillustrates embodiments in which such exchanges are performed as part ofa pre-arranged synchronization of storage spaces among the devices 2100,2500, 2600 and/or 2800.

Referring to both FIGS. 13A and 13B, such communications may include theexchange of objects for the performance of job flows that may be storedwithin the one or more federated areas 2566, such as job flowdefinitions 2220, directed acyclic graphs (DAGs) 2270, data sets 2330and/or 2370, task routines 2440, macros 2470 and/or result reports 2770.However, one or more of the devices 2100, 2500, 2600 and/or 2800 mayalso exchange, via the network 2999, other data entirely unrelated toany object stored within any federated area 2566. In variousembodiments, the network 2999 may be a single network that may extendwithin a single building or other relatively limited area, a combinationof connected networks that may extend a considerable distance, and/ormay include the Internet. Thus, the network 2999 may be based on any ofa variety (or combination) of communications technologies by whichcommunications may be effected, including without limitation, wiredtechnologies employing electrically and/or optically conductive cabling,and wireless technologies employing infrared, radio frequency (RF) orother forms of wireless transmission.

In various embodiments, each of the one or more source devices 2100 mayincorporate one or more of an input device 2110, a display 2180, aprocessor 2150, a storage 2160 and a network interface 2190 to coupleeach of the one or more source devices 2100 to the network 2999. Thestorage 2160 may store a control routine 2140, one or more job flowdefinitions 2220, one or more DAGs 2270, one or more data sets 2330, oneor more task routines 2440 and/or one or more macros 2470. The controlroutine 2140 may incorporate a sequence of instructions operative on theprocessor 2150 of each of the one or more source devices 2100 toimplement logic to perform various functions. In embodiments in whichmultiple ones of the source devices 2100 are operated together as a gridof the source devices 2100, the sequence of instructions of the controlroutine 2140 may be operative on the processor 2150 of each of thosesource devices 2100 to perform various functions at least partially inparallel with the processors 2150 of others of the source devices 2100.

In some embodiments, one or more of the source devices 2100 may beoperated by persons and/or entities (e.g., scholastic entities,governmental entities, business entities, etc.) to generate and/ormaintain analysis routines, that when executed by one or moreprocessors, causes an analysis of data to be performed. In suchembodiments, execution of the control routine 2140 may cause theprocessor 2150 to operate the input device 2110 and/or the display 2180to provide a user interface (UI) by which an operator of the sourcedevice 2100 may use the source device 2100 to develop such analysisroutines and/or to test their functionality by causing the processor2150 to execute such routines. As will be explained in greater detail, arule imposed in connection with such use of a federated area 2566 may bethat routines to be stored and/or executed therein are required to bedivided up into a combination of a set of objects, including a set oftask routines 2440 and a job flow definition 2220. Each of the taskroutines 2440 performs a distinct task, and the job flow definition 2220defines the analysis to be performed as a job flow as a combination oftasks to be performed in a particular order through the execution of theset of task routines 2440 in that particular order to thereby performthe job flow. Thus, the source device 2100 may be used in generatingsuch objects which may then be stored within one or more federated areas2566.

The tasks that each of the task routines 2440 may cause a processor toperform may include any of a variety of data analysis tasks, datatransformation tasks and/or data normalization tasks. The data analysistasks may include, and are not limited to, searches and/or statisticalanalyses that entail derivation of approximations, numericalcharacterizations, models, evaluations of hypotheses, and/or predictions(e.g., a prediction by Bayesian analysis of actions of a crowd trying toescape a burning building, or of the behavior of bridge components inresponse to a wind forces). The data transformation tasks may include,and are not limited to, sorting, row and/or column-based mathematicaloperations, row and/or column-based filtering using one or more dataitems of a row or column, and/or reordering data items within a dataobject. The data normalization tasks may include, and are not limitedto, normalizing times of day, dates, monetary values (e.g., normalizingto a single unit of currency), character spacing, use of delimitercharacters (e.g., normalizing use of periods and commas in numericvalues), use of formatting codes, use of big or little Endian encoding,use or lack of use of sign bits, quantities of bits used to representintegers and/or floating point values (e.g., bytes, words, doublewordsor quadwords), etc.

In some embodiments, the UI provided by one or more of the sourcedevices 2100 may take the form of a touch-sensitive device paired with astylus that serves to enable sketch input by an operator of a sourcedevice 2100. As will be familiar to those skilled in the art, this mayentail the combining of the display 2180 and the input device 2110 intoa single UI device that is able to provide visual feedback to theoperator of the successful sketch entry of visual tokens and of text.Through such sketch input, the operator may specify aspects of a GUIthat is to be provided during a performance of a job flow to provide aneasier and more intuitive user interface by which a user may provideinput needed for the performance of that job flow. Following recognitionand interpretation of the visual tokens and/or text within the sketchinput, a set of executable GUI instructions to implement the GUI may bestored as part of a job flow definition 2220 for such a job flow.

In some embodiments, one or more of the source devices 2100 may,alternatively or additionally, serve to assemble one or more flow inputdata sets 2330. In such embodiments, execution of the control routine2140 by the processor 2150 may cause the processor 2150 to operate thenetwork interface 2190, the input device 2110 and/or one or more othercomponents (not shown) to receive data items and to assemble thosereceived data items into one or more of the data sets 2330. By way ofexample, one or more of the source devices 2100 may incorporate and/orbe in communication with one or more sensors to receive data itemsassociated with the monitoring of natural phenomena (e.g., geological ormeteorological events) and/or with the performance of a scientific orother variety of experiment (e.g., a thermal camera or sensors disposedabout a particle accelerator). By way of another example, the processor2150 of one or more of the source devices 2100 may be caused by itsexecution of the control routine 2140 to operate the network interface2190 to await transmissions via the network 2999 from one or more otherdevices providing at least at portion of at least one data set 2330.

Regardless of the exact manner in which flow input data sets 2330 aregenerated, each flow input data set 2330 may include any of a widevariety of types of data associated with any of a wide variety ofsubjects. By way of example, each flow input data set 2330 may includescientific observation data concerning geological and/or meteorologicalevents, or from sensors employed in laboratory experiments in areas suchas particle physics. By way of another example, the each flow input dataset 2330 may include indications of activities performed by a randomsample of individuals of a population of people in a selected country ormunicipality, or of a population of a threatened species under study inthe wild.

In various embodiments, each of the one or more reviewing devices 2800may incorporate one or more of an input device 2810, a display 2880, aprocessor 2850, a storage 2860 and a network interface 2890 to coupleeach of the one or more reviewing devices 2800 to the network 2999. Thestorage 2860 may store a control routine 2840, one or more DAGs 2270,one or more data sets 2370, one or more macros 2470, one or moreinstance logs 2720, and/or one or more result reports 2770. The controlroutine 2840 may incorporate a sequence of instructions operative on theprocessor 2850 of each of the one or more reviewing devices 2800 toimplement logic to perform various functions. In embodiments in whichmultiple ones of the reviewing devices 2800 are operated together as agrid of the reviewing devices 2800, the sequence of instructions of thecontrol routine 2840 may be operative on the processor 2850 of each ofthose reviewing devices 2800 to perform various functions at leastpartially in parallel with the processors 2850 of others of thereviewing devices 2800.

In some embodiments, one or more of the reviewing devices 2800 may beoperated by persons and/or entities (e.g., scholastic entities,governmental entities, business entities, etc.) to utilize and/orperform reviews of analysis routines that have been stored in one ormore federated areas 2566 as a set of objects, such as a set of taskroutines 2440 and a job flow definition 2220. In such embodiments,execution of the control routine 2840 may cause the processor 2850 tooperate the input device 2810 and/or the display 2880 to provide a userinterface by which an operator of the reviewing device 2800 may use thereviewing device 2800 to view result reports 2770 and/or instance logs2720 generated by new and/or past performances of job flows.Alternatively, an operator of the reviewing device 2800 may use thereviewing device 2800 to audit aspects of new and/or past performancesof job flows, including selections of flow input data sets 2330 used,selections of task routines 2440 used, and/or mid-flow data sets 2370that were generated and exchanged between task routines 2440, as well asviewing result reports 2770 and/or instance logs 2720. By way ofexample, the operator of one of the reviewing devices 2800 may beassociated with a scholastic, governmental or business entity that seeksto review a performance of a job flow of an analysis that was created byanother entity. Such a review may be a peer review between two or moreentities involved in scientific or other research, and may be focused onconfirming assumptions on which algorithms were based and/or thecorrectness of the performance of those algorithms. Alternatively, sucha review may be part of an inspection by a government agency into thequality of the analyses performed by and relied upon by a business inmaking decisions and/or assessing its own financial soundness, and mayseek to confirm whether correct legally required calculations were used.

In various embodiments, each of the one or more federated devices 2500may incorporate one or more of a processor 2550, a storage 2560, one ormore neuromorphic devices 2570, and a network interface 2590 to coupleeach of the one or more federated devices 2500 to the network 2999. Thestorage 2560 may store a control routine 2540. In some embodiments, partof the storage 2560 may be allocated for at least a portion of one ormore federated areas 2566. In other embodiments, each of the one or morefederated devices 2500 may incorporate and/or be coupled to one or morestorage devices 2600 within which storage space may be allocated for atleast a portion of one or more federated areas 2566. Regardless of wherestorage space is allocated for one or more federated areas 2566, each ofthe one or more federated areas 2566 may hold one or more objects suchas one or more job flow definitions 2220, one or more DAGs 2270, one ormore flow input data sets 2330, one or more task routines 2440, one ormore macros 2470, one or more instance logs 2720, and/or one or moreresult reports 2770. In embodiments in which a job flow is performed bythe one or more federated devices 2500 within a federated area 2566,such a federated area 2566 may at least temporarily hold one or moremid-flow data sets 2370 during times when one or more of the mid-flowdata sets 2370 are generated by and exchanged between task routines 2440during the performance of the job flow. In embodiments in which a DAG2270 is generated by the one or more federated devices 2500 within afederated area 2566, such a federated area 2566 may at least temporarilyhold one or more macros 2470 during times when one or more of the macros2470 are generated as part of generating the DAG 2270.

In some embodiments that include the one or more storage devices 2600 inaddition to the one or more federated devices 2500, the maintenance ofthe one or more federated areas 2566 within such separate and distinctstorage devices 2600 may be part of an approach of specializationbetween the federated devices 2500 and the storage devices 2600. Morespecifically, there may be numerous ones of the federated devices 2500forming the grid 2005 in which each of the federated devices 2500 mayincorporate processing and/or other resources selected to better enablethe execution of task routines 2440 as part of performing job flowsdefined by the job flow definitions 2220, the generation of DAGs 2270,and/or other processing functions associated with developing, performingand/or analyzing aspects of job flows. Correspondingly, there may benumerous ones of the storage devices 2600 forming the grid 2006 in whichthe storage devices 2600 may be organized and interconnected in a mannerproviding a distributed storage system that may provide increased speedof access to objects within each of the one or more federated areas 2566through parallelism, and/or may provide fault tolerance of storage. Suchdistributed storage may also be deemed desirable to better accommodatethe storage of particularly large ones of the data sets 2330 and/or2370, as well as any particularly large data sets that may beincorporated into one or more of the result reports 2770.

The control routine 2540 may incorporate a sequence of instructionsoperative on the processor 2550 of each of the one or more federateddevices 2500 to implement logic to perform various functions. Inembodiments in which multiple ones of the federated devices 2500 areoperated together as the grid 2005 of the federated devices 2500, thesequence of instructions of the control routine 2540 may be operative onthe processor 2550 of each of the federated devices 2500 to performvarious functions at least partially in parallel with the processors2550 of others of the federated devices 2500. As will be described ingreater detail, among such functions may be the at least partiallyparallel performance of job flows defined by one or more of the job flowdefinitions 2220, which may include the at least partially parallelexecution of one or more of the task routines 2440 to perform tasksspecified by the one or more job flow definitions 2220. As will also bedescribed in greater detail, also among such functions may be theoperation of the one or more neuromorphic devices 2570 to instantiate,develop and/or utilize one or more neural networks to enableneuromorphic processing to be employed in the performance of one or moretasks and/or job flows.

Turning to FIG. 13C, as depicted, the control routine 2540 may include afederated area component 2546 to cause the processor(s) 2550 of the oneor more federated devices 2500 to maintain one or more federated areas2566 within the storage 2560 of each of the one or more federateddevices 2500 and/or within the one or more storage devices 2600. Many ofthe operations that the processor(s) 2550 of the one or more federateddevices 2500 may be caused to perform by execution of the controlroutine 2540, including the instantiation, maintenance and/orun-instantiation of the one or more federated areas 2566, may be inresponse to requests received via the network 2999 from the one or moresource devices 2100 and/or from the one or more reviewing devices 2800.Also, many of such received requests may entail the exchange of one ormore objects.

As also depicted, the control routine 2540 may also include a portalcomponent 2549 to cause the processor(s) 2550 of the one or morefederated devices 2500 to limit access to the one or more federatedareas 2566 to particular authorized persons and/or particular authorizeddevices that may be associated with one or more particular corporate,governmental, scholastic and/or other types of entities.Correspondingly, the processor(s) 2150 of the one or more source devices2100 may be caused by execution of the control routine 2140 to provide aUI that enables an operator thereof to send such requests to the one ormore federated devices 2500, and/or the processor(s) 2850 of the one ormore reviewing devices 2800 may be caused by execution of the controlroutine 2840 to provide a UI that enables an operator thereof to do so.The processor(s) 2550 of the one or more control devices 2500 may becaused by the portal component 2549 to cooperate, via the network 2999,with the requesting device 2100 or 2800 to cause the UI provided therebyto present the operator thereof with a request for a password or othersecurity credential to verify that the operator and/or the requestingdevice 2100 or 2800 is authorized to make the particular request thathas been made.

Alternatively or additionally, some interactions between a requestingdevice 2100 or 2800, including requests that may be transmitted via thenetwork 2999 to the one or more federated devices 2566, may beautomated. In embodiments in which such automated requests are made, therequesting device 2100 or 2800 may automatically provide securitycredentials to the one or more federated devices 2500 to verify that therequesting device 2100 or 2800 is authorized to make the particularrequest that has been made.

As further depicted, the control routine 2540 may also include aninterpretation component 2547 to cause the processor(s) 2550 of the oneor more federated devices 2500 to, in response to any of a variety oferror conditions that may arise in performing a requested operationand/or in response to instances in which a request is to be denied,generate a graphical indication of the error and/or the cause fordenial. Such a graphical indication may take the form of a DAG 2270 thatprovides a visual indication of an error or other condition within anobject and/or between two or more objects, and may entail interpretingportions of executable instructions, definitions of job flows,specifications of input and/or output interfaces, comments written byprogrammers, etc., within such objects as job flow definitions 2220,task routines 2440 and/or instance logs 2720. Upon being generated, theprocessor(s) 2550 may be caused by the portal component 2549 to relaysuch graphical indications (e.g., DAGs 2270) to the requesting device tobe visually presented to an operator thereof and/or stored therein for afuture visual presentation to an operator thereof.

Among such requests may be a request to store one or more objects withina federated area 2566, to access one or more objects stored within afederated area 2566 and/or to delete one or more objects stored within afederated area 2566. As depicted, the control routine 2540 may includean admission component 2542 to cause the processor(s) 2550 of the one ormore federated devices 2500 to apply a set of rules that placeconstraints on the storage of objects within federated areas and/or theremoval of objects therefrom to ensure that job flows are able to befully performed and/or that past performances of job flows are able tobe repeated as part of being scrutinized. In so applying such rules, theprocessor(s) 2550, in response to the request, may fully or partiallycarry out the requested operations, which may result in the exchange ofone or more objects via the network 2999 between the requesting device2100 or 2800 and the one or more federated devices 2500, depending onthe application of such a set of rules. Alternatively, in response, theprocessor(s) 2550 may transmit an indication of a refusal, via thenetwork 2999 and to the requesting device, to carry out the requestedoperations, depending on the application of such a set of rules. Such anindication may include a DAG 2270 that visually presents an indicationof the reason for the refusal.

Among such requests may be a request for the one or more federateddevices 2500 to convert a spreadsheet data structure into a set ofobjects required for the performance of an analysis as a job flow, andto store those generated objects within a federated area 2566. Such aspreadsheet data structure may contain one or more two-dimensionalarrays of data and multiple formulae for the performance of theanalysis. In response, the processor(s) 2550 of the one or morefederated devices 2500 may analyze the included data and the formulae toderive a set of task routines and a job flow definition that is able toperform the analysis specified in the data structure in a manner thatmay be better optimized for a performance of the analysis as a job flowusing distributed processing resources of the one or more federateddevices 2500. Additionally, the processor(s) 2550 may generate a DAG2270 as a visual guide of the resulting job flow.

Among such requests may be a request for the processor(s) 2550 of theone or more federated devices 2500 to perform a job flow. As will beexplained in greater detail, where the request is to repeat a particularpast performance of a job flow, the processor(s) 2550 of the one or morefederated devices may, in response, may use the information included inthe request that identifies the job flow to retrieve the various objectsassociated with the past performance (e.g., the job flow definition2220, the flow input data set(s) 2330, the task routines 2440) from oneor more federated areas 2566, and may then use the retrieved objects torepeat the past performance. In some embodiments, the processor(s) 2550may also retrieve the results report(s) 2770 generated by the pastperformance for comparison with the corresponding result report(s) 2770generated by the repeat performance, and may transmit an indication ofthe results thereof to the requesting device 2100 or 2800. Such anindication of the results may include a DAG 2270 that may provide avisual indication of any inconsistency identified by the comparison.

Alternatively, where the request is to perform a job flow anew (i.e., isnot a request to repeat a past performance of a job flow), theprocessor(s) 2550, in response, may retrieve the various objects neededfor the performance, including the most up to date versions of the taskroutines 2440 needed to perform each of the tasks specified in the jobflow definition 2220 for the job flow. The processor(s) 2550 mayadditionally check whether the job flow has already been performed withthe same set of most up to date task routines 2440, and if so, may thentransmit the result report(s) 2770 of that past performance to therequesting device 2100 or 2800 in lieu of performing what would be arepetition of that past performance.

Among such requests may be a request for the one or more federateddevices 2500 to generate a DAG 2270 of one or more objects, such as aDAG 2270 of one or more task routines 2440, the task(s) performed by oneor more task routines 2440, a job flow specified in a job flowdefinition 2220, or a past performance of a job flow documented by aninstance log 2720. A DAG 2270 may provide visual representations of oneor more tasks and/or task routines 2440, including visualrepresentations of inputs and/or outputs of each. In response, theprocessor(s) 2550 of the one or more federated devices 2500 may generatethe requested DAG 2270 and transmit it the requesting device 2100 or2800. As an alternative to a request to generate a DAG 2270 using theprocessing resources of the one or more federated devices 2500, arequest may be received for the one or more federated devices 2500 toprovide the requesting device 2100 or 2800 a set of objects needed toenable the requesting device 2100 or 2800 to generate a DAG 2270. Inresponse, the processor(s) 2550 of the one or more federated devices2500 may generate a set of macros 2470, one for each task or taskroutine 2440 that is to be included in the DAG 2270 for purposes ofbeing transmitted to the requesting device 2100 or 2800 to enablegeneration of the DAG 2270 by the requesting device 2100 or 2800.

Among such requests may be a request to generate a package containingcopies of one or more of the federated areas 2566 maintained by the oneor more federated devices 2500 to enable the copies of the one or morefederated areas 2566 to be instantiated within one or more otherdevices. The request may specify that each copy of a federated area 2566that is within the package is to include copies of all of the objectspresent within the counterpart federated area 2566 from which the copyis generated. Alternatively, the request may specify that each of copyof a federated area that is within the package is to include copies ofobjects present within the counterpart federated area 2566 from whichthe copy is generated that are needed to perform a specified job flowand/or that are needed to repeat a specified past performance of a jobflow. In some embodiments, the processor(s) 2550 of the one or morefederated devices 2500 may, in response, apply a set of rules to thegeneration of the package to ensure that the copies of federated area(s)included therein and/or the copies of sets of objects included withineach copy of a federated area 2566 is complete enough to avoid one ormore job flows being rendered incapable of being performed as a resultof copies of one or more needed objects not having been included in thepackage. Following generation of the package, the processor(s) 2550 maytransmit the package to the requesting device 2100 or 2800.

Turning to FIG. 13D, as an alternative to the use of separate requeststo bring about individual transfers of one or more objects to and fromthe one or more federated devices 2500, a single request may be made andgranted by the processor(s) 2550 of the one or more federated devices2500 to instantiate a synchronization relationship between a transferarea 2666 instantiated within a specified federated area 2566 maintainedby the one or more federated devices 2500, and another transfer area2166 or 2866 instantiated within the storage 2160 or 2860 of a sourcedevice 2100 or a reviewing device 2800, respectively. The transfer area2666 may occupy the entirety of the federated area 2566 within which itis instantiated, or a designated portion thereof. Correspondingly, thetransfer area 2166 or 2866 may occupy a designated portion of thestorage 2160 or 2860, respectively. With such a synchronizationrelationship in place, the contents of the transfer area 2666 may berecurringly synchronized with the contents of the transfer area 2166 or2866. More specifically, changes made to objects within the transferarea 2666 (e.g., the addition, removal and/or alteration of objects) maytrigger the transfer of one or more objects therefrom to the transferarea 2166 or 2866 to cause the contents of these two transfer areas toremain synchronized with each other. Correspondingly, changes made toobjects within the transfer area 2166 or 2866 may trigger a similartransfer of one or more objects therefrom to the transfer area 2666 toalso cause the contents of these two transfer areas to remainsynchronized with each other.

In some embodiments, processor(s) 2550 of the one or more federateddevices 2500 may cooperate with the other device 2100 or 2800 in thetriggering of such transfers by recurringly exchanging indications ofthe current state of the objects stored in their respective ones of thetransfer areas 2666, and 2166 or 2866. By way of example, a pollingapproach may be used in which the one or more federated devices 2500 maybe provided with the security credentials required to “log in” to theother device 2100 or 2800 to gain access to the transfers space 2166 or2866 in a manner similar to that of a user of the other device 2100 or2800, and may then compare what objects are present within the transferspace 2166 or 2866, respectively, to what objects were present duringthe last time such a check was performed to identify added objects,altered objects and/or removed objects therein. Correspondingly, as analternative, the other device 2100 or 2800 may be provided with similarcredentials to enable the processor(s) 2150 or 2850 thereof to “log in”to the one or more federated devices 2500 to make similar comparisonsconcerning the objects that are present within the transfer space 2666.Where a change in one of these transfer areas has been determined tohave occurred, the one of these devices that has “logged in” to theother may then make a request of the other to provide the copies of oneor more objects that are needed to bring its own one of these transferareas back into synchronization with the other such that both of thesetransfer areas again contain the same objects in the same condition.

In other embodiments, as an alternative to or in addition to such apolling approach, an approach of “volunteering” indications may be usedin which the processor(s) 2550 of the one or more federated devices 2500may, either at a recurring interval of time or in response to theoccurrence of changes to one or more objects within the transfer area2666, transmit an indication of the current state of objects currentlypresent within the transfer area 2666 to the other device 2100 or 2800.Where there has been such a change within the transfer area 2666, such atransmitted indication thereof may be accompanied with the transmissionof one or more copies of the objects that are present within thetransfer area 2566 to the other device 2100 or 2800 to enable theprocessor(s) 2150 or 2850 of the other device 2100 or 2800 to bring thetransfer area 2166 or 2866, respectively, back into synchronization withthe transfer area 2666 such that both of these transfer areas againcontain the same objects in the same condition. Correspondingly, theprocessor(s) 2150 or 2850 may be use such a “volunteering” approach insimilarly transmitting an indication of the current state of the objectscurrently present within the transfer area 2166 or 2866 to the one ormore federated devices 2500, either at a recurring interval of time orin response to the occurrence of changes to one or more objects withinthe transfer area 2166 or 2866, respectively. Similarly, where there hasbeen such a change within the transfer area 2166 or 2866, such atransmitted indication thereof may be accompanied with the transmissionof one or more copies of the objects that are present within thetransfer area 2166 or 2866 to the one or more federated devices 2500 toenable the processor(s) 2550 of the one or more federated devices 2500to bring the transfer area 2666 back into synchronization with thetransfer area 2166 or 2866, respectively, such that both of thesetransfer areas again contain the same objects in the same condition.

In some embodiments, the processor(s) 2550 of the one or more federateddevices 2500 may be caused by the admission component 2542 to apply thesame set of rules restricting the storage of objects within the one ormore federated areas and/or the removal of objects therefrom as weredescribed above in handling responses to received requests. However, inother embodiments and as will be explained in greater detail,accommodating such a synchronization relationship may entail changes to,or relaxation of, the enforcement of that set of rules. In such otherembodiments, instead of applying the set of rules in a manner thatdisallows the transfer of objects in response to an error condition orother violation of the rules, a DAG 2270 may be generated that providesa visual indication of the rule violation and/or the error condition.Upon being generated, the processor(s) 2550 may be caused by the portalcomponent 2549 to automatically transfer such a DAG 2270 between the twotransfer areas as part of the synchronization relationship and to makesuch a DAG 2270 available in both transfer areas.

In some embodiments, such a synchronization relationship may beinstantiated where the device 2100 or 2800 is at least partially used asa repository for objects, such as a source code repository for ananalysis routine that is under development. As will also be explained ingreater detail, it may be that developers who are familiar with the useof federated areas 2566 and/or who have been granted access to the oneor more federated areas 2566 maintained by the one or more federateddevices 2500 may be working in collaboration with other developers whoare not so familiar with the use of federated areas 2566 and/or who havenot been granted such access. Through such a synchronizationrelationship, objects developed by such other developers may becontributed to the objects stored within the one or more federated areas2566 by placing them within the transfer area 2166 or 2866.Correspondingly, such other developers may be given access to objectsstored within the one or more federated areas 2566 by placing thoseobjects (or copies thereof) within the transfer area 2566.

As will further be explained in greater detail, such other developersmay also not be familiar with a primary programming language that maynormally be expected to be used in generating task routines 2440 and/orjob flow definitions 2220, and may generate such objects in one or moresecondary programming languages. Thus, as part of performing suchautomated transfers and applying the set of rules, the processor(s) 2550of the one or more federated devices 2500 may also perform automatedtranslations of at least portions of objects that define or implementinput and/or output interfaces from the primary and secondaryprogramming languages, and into an intermediate representation, such asan intermediate programming language or a data structure, to enable theearlier described comparisons among definitions and/or implementationsof input and/or output interfaces to be made.

FIG. 14A illustrates a block diagram of another example embodiment of adistributed processing system 2000 also incorporating one or more sourcedevices 2100, one or more reviewing devices 2800, one or more federateddevices 2500 that may form the federated device grid 2005, and/or one ormore storage devices 2600 that may form the storage device grid 2006.FIG. 14B illustrates exchanges, through a network 2999, ofcommunications among the devices 2100, 2500, 2600 and/or 2800 associatedwith the controlled storage of and/or access to various objects withinone or more federated areas 2566. The example distributed processingsystem 2000 of FIGS. 14A-B is substantially similar to the exampleprocessing system 2000 of FIGS. 13A-B, but featuring an alternateembodiment of the one or more federated devices 2500 providing anembodiment of the one or more federated areas 2566 within which jobflows are not performed. Thus, while task routines 2440 may be executedby the one or more federated devices 2500 within each of the one or morefederated areas 2566 in addition to storing objects within each of theone or more federated areas 2566 of FIGS. 13A-B, in FIGS. 14A-B, each ofthe one or more federated areas 2566 serves as a location in whichobjects may be stored, but within which no task routines 2440 areexecuted.

Instead, in the example distributed processing system 2000 of FIGS.14A-B, the performance of job flows, including the execution of taskroutines 2440 of job flows, may be performed by the one or more sourcedevices 2100 and/or by the one or more reviewing devices 2800. Thus, asbest depicted in FIG. 14B, the one or more source devices 2100 may beoperated to interact with the one or more federated devices 2500 to moresimply store a variety of objects associated with the performance of ajob flow within the one or more source devices 2100. More specifically,one of the source devices 2100 may be operated to store, in a federatedarea 2566, a result report 2770 and/or an instance log 2720 associatedwith a performance of a job flow defined by a job flow definition 2220,in addition to also being operated to store the job flow definition2220, along with the associated task routines 2440 and any associateddata sets 2330 in a federated area 2566. Additionally, such a one of thesource devices 2100 may also store any DAGs 2270 and/or macros 2470 thatmay be associated with those task routines 2440. As a result, each ofthe one or more federated areas 2566 is employed to store a record ofperformances of job flows that occur externally thereof.

Correspondingly, as part of a review of a performance of a job flow, theone or more reviewing devices 2800 may be operated to retrieve the jobflow definition 2220 of the job flow, along with the associated taskroutines 2440 and any associated data sets 2330 from a federated area2566, in addition to retrieving the corresponding result report 2770generated by the performance and/or the instance log 2720 detailingaspects of the performance With such a more complete set of the objectsassociated with the performance retrieved from one or more federatedareas 2566, the one or more reviewing devices 2800 may then be operatedto independently repeat the performance earlier carried out by the oneor more source devices 2100. Following such an independent performance,a new result report 2870 generated by the independent performance maythen be compared to the retrieved result report 2770 as part ofreviewing the outputs of the earlier performance. Where macros 2470and/or DAGs 2270 associated with the associated task routines 2440 areavailable, the one or more reviewing devices 2800 may also be operatedto retrieve them for use in analyzing any discrepancies revealed by suchan independent performance.

Referring back to all of FIGS. 13A-B and 14A-B, the role of generatingobjects and the role of reviewing the use of those objects in a pastperformance have been presented and discussed as involving separate anddistinct devices, specifically, the source devices 2100 and thereviewing devices 2800, respectively. However, it should be noted thatother embodiments are possible in which the same one or more devices maybe employed in both roles such that at least a subset of the one or moresource devices 2100 and the one or more reviewing devices 2800 may beone and the same.

FIGS. 15A, 15B, 15C, 15D and 15E, together, illustrate aspects of theprovision of, and interactions among, multiple related federated areas2566 by the one or more federated devices 2500. FIG. 15A depicts aspectsof a linear hierarchy of federated areas 2566, FIG. 15B depicts aspectsof a hierarchical tree of federated areas 2566, and FIG. 15C depictsaspects of navigating among federated areas 2566 within the hierarchicaltree of FIG. 15B. FIGS. 15A-C, together, also illustrate aspects of oneor more relationships that may be put in place among federated areas2566 that may control access to objects stored therein. FIG. 15Dillustrates aspects of selectively allowing users of one or morefederated areas 2566 to exercise control over various aspects thereof.FIG. 15E illustrates aspects of supporting the addition of new federatedareas 2566 and/or new users of federated areas 2566, using an example ofbuilding a set of related federated areas 2566 based on the examplehierarchical tree of federated areas introduced in FIGS. 15B-C.

Turning to FIG. 15A, a set of federated areas 2566 q, 2566 u and 2566 xmay be maintained within the storage(s) 2560 of the one or morefederated devices 2500 and/or within the one or more storage devices2600. As depicted, a linear hierarchy of degrees of restriction ofaccess may be put in place among the federated areas 2566 q, 2566 u and2566 x. More specifically, the federated area 2566 q may be a privatefederated area subject to the greatest degree of restriction in accessamong the depicted federated areas 2566 q, 2566 u and 2566 x. Incontrast, the base federated area 2566 x may a more “public” federatedarea to the extent that it may be subject to the least restricted degreeof access among the depicted federated areas 2566 q, 2566 u and 2566 x.Further, the intervening federated area 2566 u may be subject to anintermediate degree of restriction in access ranging from almost asrestrictive as the greater degree of restriction applied to the privatefederated area 2566 q to almost as unrestrictive as the lesser degree ofrestriction applied to the base federated area 2566 x. Stateddifferently, the number of users granted access may be the largest forthe base federated area 2566 x, may progressively decrease to anintermediate number for the intervening federated area 2566 u, and mayprogressively decrease further to a smallest number for the privatefederated area 2566 q.

There may be any of a variety of scenarios that serve as the basis forselecting the degrees of restriction of access to each of the federatedareas 2566 q, 2566 u and 2566 x. By way of example, all three of thesefederated areas may be under the control of a user of the source device2100 q where such a user may desire to provide the base federated area2566 x as a storage location to which a relatively large number of otherusers may be granted access to make use of objects stored therein by theuser of the source device 2100 q and/or at which other users may storeobjects as a mechanism to provide objects to the user of the sourcedevice 2100 q. Such a user of the source device 2100 q may also desireto provide the intervening federated area 2566 u as a storage locationto which a smaller number of selected other users may be granted access,where the user of the source device 2100 q desires to exercise tightercontrol over the distribution of objects stored therein.

As a result of this hierarchical range of restrictions in access, a userof the depicted source device 2100 x may be granted access to the basefederated area 2566 x, but not to either of the other federated areas2566 u or 2566 q. A user of the depicted source device 2100 u may begranted access to the intervening federated area 2566 u, and asdepicted, such a user of the source device 2100 u may also be grantedaccess to the base federated area 2566 x, for which restrictions inaccess are less than that of the intervening federated area 2566 u.However, such a user of the source device 2100 u may not be grantedaccess to the private federated area 2566 q. In contrast, a user of thesource device 2100 q may be granted access to the private federated area2566 q. As depicted, may also be granted access to the interveningfederated area 2566 u and the base federated area 2566 x, both of whichare subject to lesser restrictions in access than the private federatedarea 2566 q.

As a result of the hierarchy of access restrictions just described,users granted access to the intervening federated area 2566 u aregranted access to objects 2220, 2270, 2330, 2370, 2440, 2470, 2720and/or 2770 that may be stored within either of the interveningfederated area 2566 u or the base federated area 2566 x. To enable suchusers to request the performance of job flows using objects stored ineither of these federated areas 2566 x and 2566 u, an inheritancerelationship may be put in place between the intervening federated area2566 u and the base federated area 2566 x in which objects stored withinthe base federated area 2566 x may be as readily available to beutilized in the performance of a job flow at the request of a user ofthe intervening federated area 2566 u as objects that are stored withinthe intervening federated area 2566 u.

Similarly, also as a result of the hierarchy of access restrictions justdescribed, the one or more users granted access to the private federatedarea 2566 q are granted access to objects 2220, 2270, 2330, 2370, 2440,2470, 2720 and/or 2770 that may be stored within any of the privatefederated area 2566 q, the intervening federated area 2566 u or the basefederated area 2566 x. Correspondingly, to enable such users to requestthe performance of job flows using objects stored in any of thesefederated areas 2566 x and 2566 u, an inheritance relationship may beput in place among the private federated area 2566 q, the interveningfederated area 2566 u and the base federated area 2566 x in whichobjects stored within the base federated area 2566 x or the interveningfederated area 2566 u may be as readily available to be utilized in theperformance of a job flow at the request of a user of the privatefederated area 2566 q as objects that are stored within the privatefederated area 2566 q.

Such inheritance relationships among the federated areas 2566 q, 2566 uand 2566 x may be deemed desirable to encourage efficiency in thestorage of objects throughout by eliminating the need to store multiplecopies of the same objects throughout multiple federated areas 2566 tomake them accessible throughout a hierarchy thereof. More precisely, atask routine 2440 stored within the base federated area 2566 x need notbe copied into the private federated area 2566 q to become available foruse during the performance of a job flow requested by a user of theprivate federated area 2566 q and defined by a job flow definition 2220that may be stored within the private federated area 2566 q.

In some embodiments, such inheritance relationships may be accompaniedby corresponding priority relationships to provide at least a defaultresolution to instances in which multiple versions of an object arestored in different ones of the federated areas 2566 q, 2566 u and 2566x such that one version thereof must be selected from among multiplefederated areas for use in the performance of a job flow. By way ofexample, and as will be explained in greater detail, there may bemultiple versions of a task routine 2440 that may be stored within asingle federated area 2566 or across multiple federated areas 2566. Thissituation may arise as a result of improvements being made to such atask routine 2440, and/or for any of a variety of other reasons. Where apriority relationship is in place between at least the base federatedarea 2566 x and the intervening federated area 2566 u, in addition to aninheritance relationship therebetween, and where there is a differentversion of a task routine 2440 within each of the federated areas 2566 uand 2566 x that may be used in the performance of a job flow requestedby a user of the intervening federated area 2566 u (e.g., through thesource device 2100 u), priority may be automatically given by theprocessor(s) 2550 of the one or more federated devices 2500 to using aversion stored within the intervening federated area 2566 u over usingany version that may be stored within the base federated area 2566 x.Stated differently, the processor(s) 2550 of the one or more federateddevices 2500 may be caused to search within the intervening federatedarea 2566 u, first, for a version of such a task routine 2440, and mayuse a version found therein if a version is found therein. Theprocessor(s) 2550 of the one or more federated devices 2500 may thenentirely forego searching within the base federated area 2566 x for aversion of such a task routine 2440, unless no version of the taskroutine 2440 is found within the intervening federated area 2566 u.

Similarly, where a priority relationship is in place between among allthree of the federated areas 2566 x, 2566 u and 2566 q, in addition toan inheritance relationship thereamong, and where there is a differentversion of a task routine 2440 within each of the federated areas 2566q, 2566 u and 2566 x that may be used in the performance of task of ajob flow requested by a user of the private federated area 2566 q (e.g.,through the source device 2100 q), priority may be automatically givento using the version stored within the private federated area 2566 qover using any version that may be stored within either the interveningfederated area 2566 u or the base federated area 2566 x. However, if noversion of such a task routine 2440 is found within the privatefederated area 2566 q, then the processor(s) 2550 of the one or morefederated devices 2500 may be caused to search next within theintervening federated area 2566 u for a version of such a task routine2440, and may use a version found therein if a version is found therein.However, if no version of such a task routine 2440 is found withineither the private federated area 2566 q or the intervening federatedarea 2566 u, then the processor(s) 2550 of the one or more federateddevices 2500 may be caused to search within the base federated area 2566x for a version of such a task routine 2440, and may use a version foundtherein if a version is found therein.

In some embodiments, inheritance relationships may be accompanied bycorresponding dependency relationships that may be put in place toensure that all objects required to perform a job flow continue to beavailable. As will be explained in greater detail, for such purposes asenabling accountability and/or investigating errors in analyses, it maybe deemed desirable to impose restrictions against actions that may betaken to delete (or otherwise make inaccessible) objects stored within afederated area 2566 that are needed to perform a job flow that isdefined by a job flow definition 2220 within that same federated area2566. Correspondingly, where an inheritance relationship is put in placeamong multiple federated areas 2566, it may be deemed desirable to put acorresponding dependency relationship in place in which similarrestrictions are imposed against deleting (or otherwise makinginaccessible) an object in one federated area 2566 that may be neededfor the performance of a job flow defined by a job flow definition 2220stored within another federated area 2566 that is related by way of aninheritance relationship put in place between the two federated areas2566. More specifically, where a job flow definition 2220 is storedwithin the intervening federated area 2566 u that defines a job flowthat requires a task routine 2440 stored within the base federated area2566 x (which is made accessible from within the intervening federatedarea 2566 u as a result of an inheritance relationship with the basefederated area 2566 x), the processor(s) 2550 of the one or morefederated devices 2500 may not permit the task routine 2440 storedwithin the base federated area 2566 x to be deleted. However, in someembodiments, such a restriction against deleting the task routine 2440stored within the base federated area 2566 x may cease to be imposed ifthe job flow definition 2220 that defines the job flow that requiresthat task routine 2440 is deleted, and there are no other job flowdefinitions 2220 stored elsewhere that also have such a dependency onthat task routine 2440.

Similarly, where a job flow definition 2220 is stored within the privatefederated area 2566 q that defines a job flow that requires a taskroutine 2440 stored within either the intervening federated area 2566 uor the base federated area 2566 x (with which there may be aninheritance relationship), the processor(s) of the one or more federateddevices 2500 may not permit that task routine 2440 to be deleted.However, such a restriction against deleting that task routine 2440 maycease to be imposed if the job flow definition 2220 that defines the jobflow that requires that task routine 2440 is deleted, and there are noother job flow definitions 2220 stored elsewhere that also have such adependency on that task routine 2440.

In concert with the imposition of inheritance and/or priorityrelationships among a set of federated areas 2566, the exact subset offederated areas 2566 to which a user is granted access may be used as abasis to automatically select a “perspective” from which job flows maybe performed by the one or more federated devices 2500 at the request ofthat user. Stated differently, where a user requests the performance ofa job flow, the retrieval of objects required for that performance maybe based, at least by default, on what objects are available at thefederated area 2566 among the one or more federated areas 2566 to whichthe user is granted access that has highest degree of accessrestriction. The determination of what objects are so available may takeinto account any inheritance and/or priority relationships that may bein place that include such a federated area 2566. Thus, where a usergranted access to the private federated area 2566 q requests theperformance of a job flow, the processor(s) 2550 of the federateddevices 2500 may be caused to select the private federated area 2566 qas the perspective on which determinations concerning which objects areavailable for use in that performance will be based, since the federatedarea 2566 q is the federated area 2566 with the most restricted accessthat the user has been granted access to within the depicted linearhierarchy of federated areas 2566. With the private federated area 2566q so selected as the perspective, any inheritance and/or priorityrelationships that may be in place between the private federated area2566 q and either of the intervening federated area 2566 u or the basefederated area 2566 x may be taken into account in determining whetherany objects stored within either are to be deemed available for use inthat performance (which may be a necessity if there are any objects thatare needed for that performance that are not stored within the privatefederated area 2566 q).

Alternatively or additionally, in some embodiments, such an automaticselection of perspective may be used to select the storage space inwhich a performance takes place. Stated differently, as part ofmaintaining the security that is intended to be provided through theimposition of a hierarchy of degrees of access restriction acrossmultiple federated areas 2566, a performance of a job flow requested bya user may, at least by default, be performed within the federated areathat has the highest degree of access restriction among the one or morefederated areas to which that user has been granted access. Thus, wherea user granted access to the private federated area 2566 q requests aperformance of a job flow by the one or more federated devices 2500,such a requested performance of that job flow may automatically be soperformed by the processor(s) 2550 of the one or more federated devices2500 within the storage space of the private federated area 2566 q. Inthis way, aspects of such a performance are kept out of reach from otherusers that have not been granted access to the private federated area2566 q, including any objects that may be generated as a result of sucha performance (e.g., mid-flow data sets 2370, result reports 2770,etc.). Such a default selection of a federated area 2566 having morerestricted access in which to perform a job flow may be based on apresumption that each user will prefer to have the job flow performancesthat they request being performed within the most secure federated area2566 to which they have been granted access.

It should be noted that, although a linear hierarchy of just threefederated areas is depicted in FIG. 15A for sake of simplicity ofdepiction and discussion, other embodiments of a linear hierarchy arepossible in which there may be multiple intervening federated areas 2566of progressively changing degree of restriction in access between thebase federated area 2566 x and the private federated area 2566 q.Therefore, the depicted quantity of federated areas should not be takenas limiting.

It should also be noted that, although just a single source device 2100is depicted as having been granted access to each of the depictedfederated areas 2566, this has also been done for sake of simplicity ofdepiction and discussion, and other embodiments are possible in whichaccess to one or more of the depicted federated areas 2566 may begranted to users of more than one device. More specifically, the mannerin which restrictions in access to a federated area 2566 may beimplemented may be in any of a variety of ways, including and notlimited to, restricting access to one or more particular users (e.g.,through use of passwords or other security credentials that areassociated with particular persons and/or with particular organizationsof people), or restricting access to one or more particular devices(e.g., through certificates or security credentials that are storedwithin one or more particular devices that may be designated for use ingaining access).

Turning to FIG. 15B, a larger set of federated areas 2566 m, 2566 q,2566 r, 2566 u and 2566 x may be maintained within the storage(s) 2560of the one or more federated devices 2500 and/or within the one or morestorage devices 2600. As depicted, a tree-like hierarchy of degrees ofrestriction of access, similar to the hierarchy depicted in FIG. 15A,may be put in place among the federated areas 2566 within each ofmultiple branches and/or sub-branches of the depicted hierarchical tree.More specifically, each of the federated areas 2566 m, 2566 q and 2566 rmay be a private federated area subject to the highest degrees ofrestriction in access among the depicted federated areas 2566 m, 2566 q,2566 r, 2566 u and 2566 x. Again, in contrast, the base federated area2566 x may be a more public federated area to the extent that it may besubject to the least restricted degree of access among the depictedfederated areas 2566 m, 2566 q, 2566 r, 2566 u and 2566 x. Further, theintervening federated area 2566 u interposed between the base federatedarea 2566 x and each of the private federated areas 2566 q and 2566 rmay be subject to an intermediate degree of restriction in accessranging from almost as restrictive as the degree of restriction appliedto either of the private federated areas 2566 q or 2566 r to almost asunrestrictive as the degree of restriction applied to the base federatedarea 2566 x. Thus, as in the case of the linear hierarchy depicted inFIG. 15A, the number of users granted access may be the largest for thebase federated area 2566 x, may progressively decrease to anintermediate number for the intervening federated area 2566 u, and mayprogressively decrease further to smaller numbers for each of theprivate federated areas 2566 m, 2566 q and 2566 r. Indeed, thehierarchical tree of federated areas 2566 of FIG. 15B shares many of thecharacteristics concerning restrictions of access of the linearhierarchy of federated areas 2566 of FIG. 15A, such that the linearhierarchy of FIG. 15A may be aptly described as a hierarchical treewithout branches.

As a result of the depicted hierarchical range of restrictions inaccess, a user of the depicted source device 2100 x may be grantedaccess to the base federated area 2566 x, but not to any of the otherfederated areas 2566 m, 2566 q, 2566 r or 2566 u. A user of the depictedsource device 2100 u may be granted access to the intervening federatedarea 2566 u, and may also be granted access to the base federated area2566 x, for which restrictions in access are less than that of theintervening federated area 2566 u. However, such a user of the sourcedevice 2100 u may not be granted access to any of the private federatedareas 2566 m, 2566 q or 2566 r. In contrast, a user of the source device2100 q may be granted access to the private federated area 2566 q, andmay also granted access to the intervening federated area 2566 u and thebase federated area 2566 x, both of which are subject to lesserrestrictions in access than the private federated area 2566 q. A user ofthe source device 2100 r may similarly be granted access to the privatefederated area 2566 r, and may similarly also be granted access to theintervening federated area 2566 u and the base federated area 2566 x.Additionally, a user of the source device 2100 m may be granted accessto the private federated area 2566 m, and may also be granted access tothe base federated area 2566 x. However, none of the users of the sourcedevices 2100 m, 2100 q and 2100 r may be granted access to the others ofthe private federated areas 2566 m, 2566 q and 2566 r.

As in the case of the linear hierarchy of FIG. 15A, within the depictedbranch 2569 xm, one or more of inheritance, priority and/or dependencyrelationships may be put in place to enable objects stored within thebase federated area 2566 x to be accessible from the private federatedarea 2566 m to the same degree as objects stored within the privatefederated area 2566 m. Similarly, within the depicted branch 2569 xqr,and within each of the depicted sub-branches 2569 uq and 2569 ur, one ormore of inheritance, priority and/or dependency relationships may be putin place to enable objects stored within either of the interveningfederated area 2566 u and the base federated area 2566 x to beaccessible from the private federated areas 2566 q and 2566 r to thesame degree as objects stored within the private federated areas 2566 qand 2566 r, respectively.

Turning to FIG. 15C, the same hierarchical tree of federated areas 2566m, 2566 q, 2566 r, 2566 u and 2566 x of FIG. 15B is again depicted toillustrate an example of the use of human-readable forms ofidentification to enable a person to distinguish among multiplefederated areas 2566, and to navigate about the hierarchical tree towarda desired one of the depicted federated areas 2566 m, 2566 q, 2566 r,2566 u or 2566 x. More specifically, each of the federated areas 2566 m,2566 q, 2566 r, 2566 u and 2566 x may be assigned a human-readabletextual name such as the depicted textual names “mar_(t)′”, “queen”,“roger”, “uncle” and “x-ray”, respectively. In some embodiments, each ofthese human-readable names may be stored and maintained as ahuman-readable federated area identifier 2568, where the human-readabletext of each such human-readable FA identifier 2568 may have any of avariety of meanings to the persons who assign and use them, includingand not limited to, indications of who each of these federated areas2566 belongs to, what the purpose of each of these federated areas 2566is deemed to be, how each of these federated areas 2566 relates to theothers functionally and/or in terms of location within the depictedtree, etc.

In this depicted example, these depicted human-readable FA identifiers2568 have been created to also serve as part of a system of navigationin which a web browser of a remote device (e.g., one of the devices 2100or 2800) may be used with standard web access techniques through thenetwork 2999 to navigate about the depicted tree. More specifically,each of these human-readable FA identifiers 2568 may form at least partof a corresponding URL that may be structured to provide an indicationof where its corresponding one of these federated areas 2566 is locatedwithin the hierarchical tree. By way of example, the URL of the basefederated area 2566 x, which is located at the root of the tree, mayinclude the name “x-ray” of the base federated area 2566 x, but notinclude any of the names assigned to any other of these federated areas.In contrast, each of the URLs of each of the private federated areaslocated at the leaves of the hierarchical tree may be formed, at leastpartially, as a concatenation of the names of the federated areas thatare along the path from each such private federated area at a leaflocation of the tree to the base federated area 2566 x at the root ofthe tree. By way of example, the private federated area 2566 r may beassigned a URL that includes the names of the private federated area2566 r, the intervening federated area 2566 u and the base federatedarea 2566 x, thereby providing an indication of the entire path from theleaf position of the private federated area 2566 r within the tree tothe root position of the base federated area 2566 x.

In some embodiments, either in lieu of the assignment of human-readableFA identifiers 2568, or in addition to the assignment of human-readableFA identifiers 2568, each federated area 2566 may alternatively oradditionally be assigned a global federated area identifier 2569 (GUID)that is intended to be unique across all federated areas 2566 that maybe instantiated around the world. In some of such embodiments, suchuniqueness may be made at least highly likely by generating each suchglobal FA identifier 2569 as a random number or other form of randomlygenerated set of bits with a relatively large bit width such that thepossibility of two federated areas 2566 ever being assigned the sameglobal FA identifier 2569 is deemed sufficiently small that each globalFA identifiers 2569 is deemed, for all practical purposes, to be uniqueacross the entire world. Such practically unique global FA identifiers2569 may be so generated and assigned to each federated area 2566 inaddition to the human-readable FA identifiers 2568 to provide amechanism by which each federated area 2566 will always remain uniquelydistinguishable from all others, regardless of any situation that mayarise where two or more federated areas 2566 are somehow given identicalhuman-readable FA identifiers 2568.

It should be noted that, unlike the human-readable FA identifiers 2568that may be manually entered and assigned by an operator of anotherdevice (e.g., one of the devices 2100 or 2800) that may be incommunication with the one or more federated devices 2500 via thenetwork 2999, the global FA identifiers 2569 may be automaticallygenerated by the one or more federated devices 2500 as part of theinstantiation of any new federated area 2566. Such automatic generationof the global FA identifiers 2569 as part of instantiating any newfederated area 2566 may be deemed desirable to ensure that suchpractically unique identification functionality is provided for eachfederated area 2566 from the very moment that it exists. This may alsobe deemed desirable to provide some degree of continuity in the uniqueidentification of each federated area 2566 throughout the time itexists, since in some embodiments, the human-readable FA identifiers2568 may be permitted to be changed throughout the time it exists.

Turning to FIG. 15D, the control routine 2540 executed by processor(s)2550 of the one or more federated devices 2500 may include a federatedarea component 2546 to control the instantiation of, maintenance of,relationships among, and/or un-instantiation of federated areas 2566within the storage 2560 of one or more federated devices 2500 and/orwithin one or more of the storage devices 2600. The control routine 2540may also include a portal component 2549 to restrict access to the oneor more federated areas 2566 to only authorized users (e.g., authorizedpersons, entities and/or devices), and may restrict the types ofaccesses made to only the federated area(s) 2566 for which each userand/or each device is authorized. However, in alternate embodiments,control of access to the one or more federated areas 2566 may beprovided by one or more other devices that may be interposed between theone or more federated devices 2500 and the network 2999, or that may beinterposed between the one or more federated devices 2500 and the one ormore storage devices 2600 (if present), or that may still otherwisecooperate with the one or more federated devices 2500 to do so.

In executing the portal component 2549, the processor(s) 2550 of the oneor more federated devices 2500 may be caused to operate one or more ofthe network interfaces 2590 to provide a portal accessible by otherdevices via the network 2999 (e.g., the source devices 2100 and/or thereviewing devices 2800), and through which access may be granted to theone or more federated areas 2566. In some embodiments in which the oneor more federated devices 2500 additionally serve to control access tothe one or more federated areas 2566, the portal may be implementedemploying the hypertext transfer protocol over secure sockets layer(HTTPS) to provide a website securely accessible from other devices viathe network 2999. Such a website may include a webpage generated by theprocessor 2550 that requires the provision of a password and/or othersecurity credentials to gain access to the one or more federated areas2566. Such a website may be configured for interaction with otherdevices via an implementation of representational state transfer (RESTor RESTful) application programming interface (API). However, otherembodiments are possible in which the processor 2550 may provide aportal accessible via the network 2999 that is implemented in any of avariety of other ways using any of a variety of handshake mechanismsand/or protocols to selectively provide secure access to the one or morefederated areas 2566.

Regardless of the exact manner in which a portal may be implementedand/or what protocol(s) may be used, in determining whether to grant ordeny access to the one or more federated areas 2566 to another devicefrom which a request for access has been received, the processor(s) 2550of the one or more federated devices 2500 may be caused to refer toindications stored within portal data 2539 of users authorized to begranted access. Such indications may include indications of securitycredentials expected to be provided by such persons, entities and/ormachines. In some embodiments, such indications within the portal data2539 may be organized into a database of accounts that are eachassociated with an entity with which particular persons and/or devicesmay be associated. The processor(s) 2550 may be caused to employ theportal data 2539 to evaluate security credentials received inassociation with a request for access to the at least one of the one ormore federated areas 2566, and may operate a network interface 2590 ofone of the one or more federated devices 2500 to transmit an indicationof grant or denial of access to the at least one requested federatedarea 2566 depending on whether the processor(s) 2550 determine thataccess is to be granted.

Beyond selective granting of access to the one or more federated areas2566 (in embodiments in which the one or more federated devices 2500control access thereto), the processor(s) 2550 may be further caused byexecution of the portal component 2549 to restrict the types of accessgranted, depending on the identity of the user to which access has beengranted. By way of example, the portal data 2539 may indicate thatdifferent users are each to be allowed to have different degrees ofcontrol over different aspects of one or more federated areas 2566. Auser may be granted a relatively high degree of control such that theyare able to create and/or remove one or more federated areas 2566, areable to specify which federated areas 2566 may be included in a set offederated areas, and/or are able to specify aspects of relationshipsamong one or more federated areas 2566 within a set of federated areas.Alternatively or additionally, a user may be granted a somewhat morelimited degree of control such that they are able to alter the accessrestrictions applied to one or more federated areas 2566 such that theymay be able to control which users have access each of such one or morefederated areas 2566.

The processor(s) 2550 may be caused by execution of the portal component2549 to store indications of such changes concerning which users haveaccess to which federated areas 2566 and/or the restrictions applied tosuch access as part of the portal data 2539, where such indications maytake the form of sets of correlations of authorized users to federatedareas 2566 and/or correlations of federated areas 2566 to authorizedusers. In such indications of such correlations, either or both of thehuman-readable FA identifiers 2568 or the global FA identifiers 2569 maybe used. Where requests to add, remove and/or alter one or morefederated areas 2566 are determined, through execution of the portalcomponent 2549 to be authorized, the processor(s) 2550 may be caused byexecution of the federated area component 2546 to carry out suchrequests.

FIG. 15E depicts an example of a series of actions that the processor(s)2550 are caused to take in response to the receipt of a series ofrequests to add federated areas 2566 that eventually results in thecreation of the tree of federated areas 2566 depicted in FIGS. 15B-C. Asdepicted, the processor(s) 2550 of the one or more federated devices2500 may initially be caused to instantiate and maintain both theprivate federated area 2566 m and the base federated area 2566 x as partof a set of related federated areas that form a linear hierarchy ofdegrees of access restriction therebetween. In some embodiments, thedepicted pair of federated areas 2566 m and 2566 x may have been causedto be generated by a user of the source device 2100 m having sufficientaccess permissions (as determined via the portal component 2549) as tobe able to create the private federated area 2566 m for private storageof one or more objects that are meant to be accessible by a relativelysmall number of users, and to create the related public federated area2566 x for storage of objects meant to be made more widely availablethrough the granting of access to the base federated area 2566 x to alarger number of users. Such access permissions may also include thegranted ability to specify what relationships may be put in placebetween the federated areas 2566 m and 2566 x, including and not limitedto, any inheritance, priority and/or dependency relationshipstherebetween. Such characteristics about each of the federated areas2566 m and 2566 x may be caused to be stored by the federated areacomponent 2546 as part of the federated area parameters 2536. Asdepicted, the federated area parameters 2536 may include a database ofinformation concerning each federated area 2566 that is caused to beinstantiated and/or maintained by the federated area component 2546. Aswith the database of accounts just earlier described as beingimplemented in some embodiments within the portal data 2539, such adatabase of information concerning federated areas 2566 within thefederated area parameters 2536 may also make use of either or both ofthe human-readable FA identifiers 2568 or the global FA identifiers 2569to identify each federated area 2566.

As an alternative to both of the federated areas 2566 m and 2566 xhaving been created and caused to be related to each other throughexpress requests by a user, in other embodiments, the processor(s) 2550of the one or more federated devices 2500 may be caused by the federatedarea component 2546, and based on rules retrieved from federated areaparameters 2536, to automatically create and configure the privatefederated area 2566 m in response to a request to add a user associatedwith the source device 2100 m to the users permitted to access the basefederated area 2566 x. More specifically, a user of the depicted sourcedevice 2100 x that may have access permissions to control variousaspects of the base federated area 2566 x may operate the source device2100 x to transmit a request to the one or more federated devices 2500,via the portal provided thereby on the network 2999, to grant a userassociated with the source device 2100 m access to use the basefederated area 2566 x. In response, and in addition to so granting theuser of the source device 2100 m access to the base federated area 2566x, the processor(s) 2550 of the one or more federated devices 2500 mayautomatically generate the private federated area 2566 m for private useby the user of the source device 2100 m. Such automatic operations maybe triggered by an indication stored in the federated area databasewithin the federated area parameters 2536 that each user that is newlygranted access to the base federated area 2566 x is to be so providedwith their own private federated area 2566. This may be deemed desirableas an approach to making the base federated area 2566 x easier to usefor each such user by providing individual private federate areas 2566within which objects may be privately stored and/or developed inpreparation for subsequent release into the base federated area 2566 x.Such users may be able to store private sets of various tools that eachmay use in such development efforts.

Following the creation of both the federated areas 2566 x and 2566 m,the processor(s) 2550 of the one or more federated devices 2500 may becaused to instantiate and maintain the private federated area 2566 q tobe part of the set of federated areas 2566 m and 2566 x. In so doing,the private federated area 2566 q is added to the set in a manner thatconverts what was a linear hierarchy into a hierarchical tree with apair of branches. As with the instantiation of the private federatedarea 2566 m, the instantiation of the private federated area 2566 q mayalso be performed by the processor(s) 2550 of the one or more federateddevices 2500 as an automated response to the addition of a user of thedepicted source device 2100 q as authorized to access the base federatedarea 2566 x. Alternatively, a user with access permissions to controlaspects of the base federated area 2566 x may operate the source device2100 x to transmit a request to the portal generated by the one or morefederated devices 2500 to create the private federated area 2566 q, withinheritance, priority and/or dependency relationships with the basefederated area 2566 x, and with access that may be limited (at leastinitially) to the user of the source device 2100 q.

Following the addition of the federated area 2566 q, the processor(s)2550 of the one or more federated devices 2500 may be caused to first,instantiate the intervening federated area 2566 u inserted between theprivate federated area 2566 q and the base federated area 2566 x, andthen instantiate the private federated area 2566 r that branches fromthe newly created intervening federated area 2566 u. In so doing, thesecond branch that was created with the addition of the privatefederated area 2566 q is expanded into a larger branch that includesboth of the private federated areas 2566 q and 2566 r in separatesub-branches.

In various embodiments, the insertion of the intervening federated area2566 u may be initiated in a request transmitted to the portal fromeither the user of the source device 2100 q or the user of the sourcedevice 2100 x, depending on which user has sufficient access permissionsto be permitted to make such a change in the relationship between theprivate federated area 2566 q and the base federated area 2566 x,including the instantiation and insertion of the intervening federatedarea 2566 u therebetween. In some embodiments, it may be necessary forsuch a request made by one of such users to be approved by the otherbefore the processor(s) 2550 of the one or more federated devices 2500may proceed to act upon it.

Such a series of additions to a hierarchical tree may be prompted by anyof a variety of circumstances, including and not limited to, a desire tocreate an isolated group of private federated areas that are all withina single isolated branch that includes an intervening federated area bywhich users associated with each of the private federated areas withinsuch a group may be able to share objects without those objects beingmore widely shared outside the group as by being stored within the basefederated area 2566 x. Such a group of users may include a group ofcollaborating developers of task routines 2440, data sets 2330 and/orjob flow definitions 2220.

As each of the federated areas 2566 m, 2566 q, 2566 r, 2566 u and 2566 xare created, each may be given a human-readable FA identifier 2568 thatmay be supplied in the requests that are received to create each of themand/or that may be supplied and/or generated in any of a variety ofother ways, including through any of a variety of user interfaces. Also,as previously discussed, regardless of the manner or circumstances inwhich each of the depicted federated areas 2566 m, 2566 q, 2566 r, 2566u or 2566 x is instantiated, in at least some embodiments, theprocessor(s) 2550 may be caused to generate a global FA identifier 2569for each of these federated areas automatically as part of each of theirinstantiations. Again, this may be deemed desirable in order to haveeach of these federated areas be immediately distinguishable by such apractically unique identifier from the moment that each begins itsexistence. In this way, such global FA identifiers 2569 may beimmediately available to be used to identify each of these federatedareas within both the federated area parameters 2536 and the portal data2539.

FIGS. 16A, 16B, 16C, 16D, 16E, 16F, 16G, 16H and 16I, together,illustrate the manner in which a set of objects may be used to defineand perform an example job flow 2200 fgh, as well as to document theresulting example performance 2700 afg 2 h of the example job flow 2200fgh. FIG. 16E additionally illustrates how information incorporated intoone of the task routines 2440 f and/or into the job flow definition 2220fgh may be used to verify the functionality of that task routine. FIG.16F additionally illustrates how a mid-flow data set may be convertedbetween two forms amidst being exchanged between two task routines toaccommodate the use of different programming languages therebetween.FIG. 16G additionally illustrates the manner in which the job flowdefinition 2200 fgh may be marked as associated with another job flowdefinition 2200 fgh-s from which the job flow definition 2200 fgh mayhave been derived by translation. FIG. 16H additionally illustrates themanner in which the job flow 2200 fgh that employs non-neuromorphicprocessing to perform a function may be marked as associated withanother job flow 2200 jk that employs neuromorphic processing to performthe same function and that was derived from the job flow 2200 fgh. FIG.16I additionally illustrates the manner in which the job flow definition2220 fgh may be generated as and/or from a DAG 2270 fgh. For sake ofease of discussion and understanding, the same example job flow 2200 fghand example performance 2700 afg 2 h of the example job flow 2200 fghare depicted throughout all of FIGS. 16A-I. Also, it should be notedthat the example job flow 2200 fgh and example performance 2700 afg 2 hthereof are deliberately relatively simple examples presented herein forpurposes of illustration, and should not be taken as limiting what isdescribed and claimed herein to such relatively simple embodiments.

As depicted, the example job flow 2200 fgh specifies three tasks thatare to be performed in a relatively simple three-step linear orderthrough a single execution of a single task routine 2440 for each task,with none of those three tasks entailing the use of neuromorphicprocessing. Also, the example job flow 2200 fgh requires a single dataset as an input data object to the first task in the linear order, maygenerate and exchange a single data set between two of the tasks, andgenerates a single result report as an output data object of the lasttask in the linear order. As also depicted, in the example performance2700 afg 2 h of the example job flow 2200 fgh, task routines 2440 f,2440 g 2 and 2440 h are the three task routines selected to be executedto perform the three tasks. Also, a flow input data set 2330 a isselected to serve as the input data object, a mid-flow data set 2370 fgmay be generated and exchanged between two of the performed tasks as amechanism to exchange data therebetween, and a result report 2770 afg 2h is the output data object to be generated as an output of theperformance 2700 afg 2 h. Again, it should be noted that otherembodiments of a job flow are possible in which there may be many moretasks to be performed, many more data objects that serve as inputsand/or many more data objects generated as outputs. It should also benoted that other embodiments of a job flow are possible in which thereis a much more complex order of the performance of tasks that mayinclude parallel and/or conditional branches that may converge and/ordiverge.

Turning to FIGS. 16A and 16B, the job flow definition 2220 fgh for theexample job flow 2200 fgh may include a flow definition 2222 thatspecifies the three tasks to be performed, the order in which they areto be performed, and which of the three tasks is to accept a data objectas an input and/or generate a data object as an output. In specifyingthe three tasks to be performed, the flow definition 2222 may use flowtask identifiers 2241, such as the depicted flow task identifiers 2241f, 2241 g and 2241 h that uniquely identify each of the three tasks. Asdepicted, there may be just a single task routine 2440 f available amongone or more federated areas 2566 to which access is granted that is ableto perform the task specified with the flow task identifier 2241 f, andtherefore, the single task routine 2440 f may be the one task routinethat is assigned the flow task identifier 2241 f to provide anindication that it is able to perform that task. Also, there may bethree task routines 2440 g 1, 2440 g 2 and 2440 g 3 available among theone or more accessible federated areas 2566 that are each able toperform the task specified with the flow task identifier 2241 g, andtherefore, each may be assigned the same flow task identifier 2241 g.Further, there may be just a single task routine 2440 h available withinthe one or more accessible federated areas 2566 that is able to performthe task specified with the flow task identifier 2241 h, resulting inthe assignment of the flow task identifier 2241 h to the single taskroutine 2440 h.

As has been discussed, the job flow definition 2220 fgh specifies thetasks to be performed in a job flow, but does not specify any particulartask routine 2440 to be selected for execution to perform any particularone of those tasks during any particular performance of the job flow.Where there are multiple task routines 2440 that are capable ofperforming a particular task, a single one of those multiple taskroutines 2440 is selected for execution to do so, and the selection thatis made may, in part, depend on the nature of the request received toperform a job flow. More specifically, the selection of a particulartask routine 2440 for execution to perform each particular task may bebased on which task routine 2440 is the newest version to perform eachtask, and/or may be based on which task routine 2440 was used in aprevious performance of each task in a specified previous performance ofa job flow. As will be explained in detail, the selection criteria thatis used to select a task routine 2440 for each task may depend onwhether an entirely new performance of a job flow is requested or arepetition of an earlier performance of a job flow is requested. Asdepicted, in the example performance 2700 afg 2 h of the example jobflow 2200 fgh, the task routine 2440 g 2 is selected from among the taskroutines 2440 g 1, 2440 g 2 and 2440 g 3 for execution to perform thetask identified with the flow task identifier 2241 g.

Alternatively or additionally, and as previously explained in connectionwith FIGS. 15A-B, in situations in which objects needed for theperformance of a job flow are distributed among multiple federated areasthat are related by inheritance and/or priority relationships, theselection of a particular task routine 2440 to perform a task from amongmultiple task routines 2440 that are each capable of performing thatsame task may, in part, be dependent upon which federated area 2566 eachof such multiple task routines 2440 are stored within. By way ofexample, FIG. 16C depicts an example situation in which objects neededto perform the job flow 2200 fgh are distributed among the federatedareas 2566 m, 2566 u and 2566 x in the example hierarchical tree offederated areas first introduced in FIGS. 15B-C. More specifically, inthis example, the data set 2330 a and the task routine 2440 g 2 arestored within the private federated area 2566 m; the task routine 2440 g3 is stored within the intervening federated area 2566 u; and the dataset 2330 b and the task routines 2440 f, 2440 g 1 and 2440 h are storedwithin the base federated area 2566 x.

As previously discussed in reference to the linear hierarchy depicted inFIG. 15A, a “perspective” from which a job flow is to be executed maybased on which federated areas 2566 are made accessible to the deviceand/or device user makes the request for the performance to occur. Asdepicted, where the request to perform the job flow 2200 fgh is receivedfrom a user granted access to the private federated area 2566 m, as wellas to the base federated area 2566 x, but not granted access to any ofthe federated areas 2566 q, 2566 r or 2566 u, the search for objects touse in the requested performance may be limited to those stored withinthe private federated area 2566 m and the base federated area 2566 x.Stated differently, the perspective that may be automatically selectedfor use in determining which federated areas 2566 are searched forobjects may be that of the private federated area 2566 m, since theprivate federated area 2566 m is the one federated area to which theuser in this example has been granted access to that is subject to themost restricted degree of access. Based on this perspective, the privatefederated area 2566 m will be searched, along with the base federatedarea 2566 x, and along with any intervening federated areas 2566therebetween, if there were any federated areas 2566 therebetween.

As a result, the task routine 2440 g 3 stored within the interveningfederated area 2566 u is entirely unavailable for use in the requestedperformance as a result of the user having no grant of access to theintervening federated area 2566 u, and this then becomes the reason whythe task routine 2440 g 3 is not selected. In contrast, as a result ofan inheritance relationship between the private federated area 2566 mand the base federated area 2566 x, the data set 2330 b and each of thetask routines 2440 f, 2440 g 1 and 2440 h stored in the based federatedarea 2566 x may each be as readily available for being used in therequested performance of the job flow 2200 fgh as the data set 2330 aand the task routine 2440 g 2 stored in the private federated area 2566m. Therefore, the task routines 2440 f and 2440 h may be selected as aresult of being the only task routines available within either federatedarea 2566 m or 2566 x that perform their respective tasks. However,although both of the flow input data sets 2330 a and 2330 b may beequally available through that same inheritance relationship, a priorityrelationship also in place between the federated areas 2566 m and 2566 xmay result in the data set 2330 a being selected as the data set used asinput, since the flow input data set 2330 a is stored within the privatefederated area 2566 m, which is searched first for the objects neededfor the requested performance, while the flow input data set 2330 b isstored within the base federated area 2566 x, which is searched afterthe search of the private federated area 2566 m. The same combination ofinheritance and priority relationships in place between the federatedareas 2566 m and 2566 x may also result in the task routine 2440 g 2stored within the private federated area 2566 m being selected, insteadof the task routine 2440 g 1 stored within the base federated area 2566x.

Turning to FIGS. 16A and 16D, the job flow definition 2220 fgh mayinclude interface definitions 2224 that specify aspects of taskinterfaces 2444 employed in communications among task the routines 2440that are selected for execution to perform the tasks of the example jobflow 2200 fgh (e.g., the task routines 2440 f, 2440 g 2 and 2440 h).Such aspects may include quantity, type, bit widths, protocols, etc., ofparameters passed from one task routine 2440 to another as part ofcommunications among task routines 2440 during their execution. As alsodepicted, the interface definitions 2224 may alternatively oradditionally specify aspects of data interfaces 2443 between taskroutines 2440 and any data objects that may be employed as an input to aperformance (e.g., the flow input data set 2330 a) and/or that may begenerated as an output of a performance (e.g., the result report 2770afg 2 h) of the example job flow 2200 fgh, such as the data exampleperformance 2700 afg 2 h. The interface definitions 2224 may alsospecify aspects of data interfaces 2443 employed by one task routine2440 to generate a data object to convey a relatively large quantity ofdata to another task routine 2440 (e.g., the mid-flow data set 2370 fgdepicted with dotted lines, and depicted as generated by task routine2440 f for use as an input to task routine 2440 g 2), and may specifyaspects of the data interface 2443 employed by the other task routine2440 to retrieve data from that same data object. Since many of thespecified aspects of the data interfaces 2443 may necessarily be closelyassociated with the manner in which data items are organized and madeaccessible within data objects, the interface definitions 2224 mayinclude organization definitions 2223 that specify such organizationaland access aspects of the data objects. Thus, as depicted in FIG. 16D,where each of the data sets 2330 a and 2370 fg (if any are present), andthe result report 2770 afg 2 h include a two-dimensional array, theorganization definitions 2223 may specify various aspects of the dataitems 2339 (e.g., data type, bit width, etc.), the rows 2333 and/or thecolumns 2334 for each these data objects.

As previously discussed, the job flow definition 2220 fgh specifiestasks to be performed and not the particular task routines 2440 to beselected for execution to perform those tasks, which provides theflexibility to select the particular task routines 2440 for each taskdynamically at the time a performance takes place. Similarly, the jobflow definition 2220 fgh also does not specify particular data objectsto be used, which provides the flexibility to select the particular dataobjects with which the job flow 2200 fgh is to be used dynamically atthe time a performance takes place. However, the interface definitions2224 do specify aspects of the interfaces among the task routines 2440,and between the task routines 2440 and data objects. The specificationof aspects of the interfaces 2443 and/or 2444 may be deemed desirable toensure continuing interoperability among task routines 2440, as well asbetween task routines 2440 and data objects, in each new performance ofa job flow 2200, even as new versions of one or more of the taskroutines 2440 and/or new data objects are created for use in laterperformances.

In some embodiments, new versions of task routines 2440 that may becreated at a later time may be required to implement the interfaces 2443and/or 2444 in a manner that exactly matches the specifications of thoseinterfaces 2443 and/or 2444 within a job flow definition 2220. However,in other embodiments, a limited degree of variation in theimplementation of the interfaces 2443 and/or 2444 by newer versions oftask routines 2440 may be permitted as long as “backward compatibility”is maintained in retrieving input data objects or generating output dataobjects through data interfaces 2443, and/or in communications withother task routines through task interfaces 2444. As will be explainedin greater detail, the one or more federated devices 2500 may employ thejob flow definitions 2220 stored within one or more federated areas 2566to confirm that new versions of task routines 2440 correctly implementtask interfaces 2444 and/or data interfaces 2443. By way of example, insome embodiments, it may be deemed permissible for an interface 2443 or2444 that receives information to be altered in a new version of a taskroutine 2440 to accept additional information from a newer data objector a newer version of another task routine 2440 if that additionalinformation is provided, but to not require the provision of thatadditional information, since older data objects don't provide thatadditional information. Alternatively or additionally, by way ofexample, it may be deemed permissible for an interface 2443 or 2444 thatoutputs information to be altered in a new version of a task routine2440 to output additional information as an additional data objectgenerated as an output, or to output additional information to a newerversion of another task routine 2440 in a manner that permits thatadditional information to be ignored by an older version of that othertask routine 2440.

Returning to FIGS. 16A and 16B, an example instance log 2720 afg 2 hthat is generated as result a of the example performance 2700 afg 2 h ofthe example job flow 2200 fgh is depicted. Although the job flowdefinition 2220 fgh does not specify particular data objects or taskroutines 2440 to be used in performances of the example job flow 2200fgh, the example instance log 2720 afg 2 h does include such details, aswell as others, concerning the example performance 2700 afg 2 h. Thus,the example instance log 2720 afg 2 h includes the job flow identifier2221 fgh for the example job flow definition 2220 fgh; the task routineidentifiers 2441 f, 2441 g 2 and 2441 h for the particular task routines2440 f, 2440 g 2 and 2440 h, respectively, that were executed in theexample performance 2700 afg 2 h; the data object identifier 2331 a forthe data set 2330 a used as an input data object; and the result reportidentifier 2771 afg 2 h for the result report 2770 afg 2 h generatedduring the example performance 2700 afg 2 h. As has been discussed, theexample instance log 2720 afg 2 h is intended to serve as a record ofsufficient detail concerning the example performance 2700 afg 2 h as toenable all of the objects associated with the example performance 2700afg 2 h to be later identified, retrieved and used to repeat the exampleperformance 2700 afg 2 h. In contrast, the job flow definition 2220 fghis intended to remain relatively open-ended for use with a variety ofdata objects and/or with a set of task routines 2440 that may changeover time as improvements are made to the task routines 2440.

Turning to FIG. 16E, in some embodiments, the input/output behavior ofeach of the task routines 2440 that may be selected and executed inperforming the job flow 2200 fgh may be verified by being monitoredduring the performance of the job flow 2200 fgh, with the observedinput/output behavior being compared to the expected input/outputbehavior. More specifically and as depicted, the control routine 2540may include a performance component 2544 operable on the processor 2550to execute executable instructions 2447 of task routines 2440 to performthe tasks specified in a job flow definition 2220, and in so doing, theperformance component 2544 may additionally instantiate a containerenvironment 2565 in which the input/output behavior of task routines2440 may be monitored, controlled and/or compared to expected behavior.Still more specifically, and as depicted in FIG. 16F as an example, theinterface definitions 2224 within the job flow definition 2220 fgh, thecomments 2448 of the task routine 2440 f and/or the executableinstructions 2447 that implement each of the depicted interfaces 2443and 2444 of the task routine 2440 f may be employed by the performancecomponent 2544 as a reference for those interfaces of the task routine2440 f. The performance component 2544 may use such a reference toinstantiate, within a federated area 2566, a container environment 2565within which the task routine 2440 f is executed during a performance ofthe job flow 2200 fgh. In some embodiments, the instantiation of thecontainer environment 2565 may be done to create an executionenvironment for the task routine for the sole purpose of monitoring whatinput/output accesses are made by the task routine 2440 f to enable acomparison to be made between observed input/output behavior of the taskroutine 2440 f and the input/output behavior that is expected of thetask routine 2440 f based on the reference description of aspects of theinterfaces 2443 and/or 2444 provided by the comments 2448, theexecutable instructions 2447 and/or the interface definitions 2224. Inother embodiments, the instantiation of the container environment 2565may be done to also create an execution environment for the task routine2440 f in which the expected input/output behavior is actually enforcedupon the task routine 2440 f such that any aberrant input/outputbehavior by the task routine 2440 f is not allowed to be fully performed(e.g., attempted input/output accesses to data structures and/orinput/output devices that go beyond the expected input/output behaviorare prevented from actually taking place). Where the observedinput/output behavior conforms to the expected input/output behavior,the input/output functionality of the task routine 2440 f may be deemedto have been verified.

Regardless of whether the container environment 2565 enforces expectedinput/output behavior in addition to monitoring the input/outputbehavior that actually occurs, the results of the comparison between theobserved input/output behavior and the expected input/output behavior(e.g., whether the input/output functionality of the task routine 2440 fis verified, or not) may be recorded in any of a variety of ways. By wayof example, in embodiments in which each task routine 2440 is storedwithin one or more federated areas 2566 through use of a database toenable more efficient retrieval of task routines 2440, the results ofthis comparison for the task routine 2440 f may be marked in an entrymaintained by such a database for the task routine 2440 f. Alternativelyor additionally, where a DAG 2270 is generated that includes a visualrepresentation of the task routine 2440 f, that representation may beaccompanied by a visual indicator of the results of this comparison.

Turning to FIG. 16F, as previously discussed, in some embodiments, thecombination of task routines 2440 that are executed during theperformance of a job flow 2200 may include task routines with executableinstructions 2447 and/or comments 2448 written in differing programminglanguages with the differing syntax, vocabulary, formatting and/orsemantic features thereof. More specifically, and as depicted, the taskroutine 2440 f may have been written in a primary programming languagethat is normally interpreted by the processor(s) 2550 of the one or morefederated devices 2500 at runtime, such that the task routine 2440 f isdesignated as task routine 2440 pf. Therefore, within the task routine2440 pf, the executable instructions 2447 p may be written in theprimary programming language, and the comments 2448 p may be writtenwith the syntax used to distinguish comments from executableinstructions in the primary programming language. As also depicted, thetask routine 2440 g 2 may have been written in a secondary programminglanguage, such that the task routine 2440 g 2 is designated as taskroutine 2440 sg 2. The secondary programming language may not be onethat is normally interpreted by the processor(s) 2550, but may still beamong a set of pre-selected secondary programming languages that theprocessor(s) 2550 may still be capable of interpreting during runtime,either in addition to or in lieu of the primary programming language.Therefore, within the task routine 2440 sg 2, the executableinstructions 2447 s may be written in the secondary programminglanguage, and the comments 2448 s may be written with the syntax used todistinguish comments from executable instructions in the secondaryprogramming language.

As will be familiar to those skilled in the art, among the differencesbetween different programming languages may be support for differentdata types and/or differences in array types, including differences indata types of items of data within arrays and/or differences inaccessing items of data therein. Thus, although the executableinstructions 2447 p of the task routine 2440 pf may have been written toimplement the depicted data output interface 2443 to generate themid-flow data set 2370 fg as an output, and although the executableinstructions 2447 s of the task routine 2440 sg 2 may have been writtento implement the depicted data input interface 2443 to receive themid-flow data set 2370 fg as an input, there may be differences in theform of the mid-flow data set 2370 fg as it is output from the form ofthe mid-flow data set 2370 fg that is needed to be accepted as input.More specifically, the mid-flow data set 2370 may be output in a formdesignated as the mid-flow data set 2370 pfg that has one or moreparticular details of its structure being dictated by the use of theprimary programming language in the executable instructions 2447 p thatdiffer somewhat from the form designated as the mid-flow data set 2370sfg that is needed to accommodate the use of the secondary programminglanguage in the executable instructions 2447 s.

To resolve such differences, the performance component 2544 may performa conversion of data structure and/or data type (e.g., serialization orde-serialization) of the mid-flow data set 2370 fg from its 2370 pfgform to its 2370 sfg form during runtime. More precisely, theperformance component 2544 may temporarily instantiate a shared memoryspace 2660 within which one of these two forms of the mid-flow data set2370 may be temporarily stored during the performance of he job flow2200 fgh. As has been discussed, it may be deemed desirable to storemid-flow data sets 2370 that are generated during the performance of ajob flow as part of enabling a subsequent analysis of the performance ofindividual tasks of that job flow by having the mid-flow data setsthereof 2370 preserved in federated area(s) 2566 along with otherobjects associated with that job flow. With the particular programminglanguage in which the executable instructions 244′7 p of the taskroutine 2440 pf having been designated as the primary programminglanguage, it may be deemed preferable to store the mid-flow data set2370 fg in the form 2370 pfg in which it was output by the task routine2440 pf, and to not consume valuable storage space in a federated area2566 by also storing the other form 2370 sfg. Thus, while the mid-flowdata set 2370 fg may be persisted in a federated area 2566 in the form2370 pfg, the other form 2370 sfg may be discarded as part ofun-instantiating the shared memory space 2660 when the performance ofthe job flow 2200 fgh is completed.

Turning to FIG. 16G, as previously discussed, it may be that portion(s)of one or more objects of a job flow 2200 were originally written in asecondary programming language that differs from the primary programminglanguage that is relied upon by the processor(s) 2550 of the one or morefederated devices 2500 to perform job flows 2200. In such situations,and as will be discussed in more detail, such portions of such objectsmay be translated from such a secondary programming language to theprimary programming language, and this may result in the generation of atranslated form of each of such objects in which the portion(s) writtenin the secondary programming language are replaced with correspondingportions in the primary programming language. As will the neuromorphicjob flow definition 2220 jk, above, it may be deemed desirable to beable to trace where a translated form of an object came from byincluding an identifier of the original form of the object from whichthe translated form was generated.

More specifically, it may be that portions of the job flow definition2220 fgh introduced in FIG. 16A was originally written in a secondaryprogramming language as the job flow definition 2220 fgh-s. As depicted,such portions may include the depicted interface definitions 2224-s(which may include the organization definitions 2223-s) and/or the GUIinstructions 2229 fgh-s. As depicted, such portions may be translatedfrom the secondary programming language to the primary programminglanguage that will be utilized during the performance 2700 afg 2 h. Inso doing, the job flow definition 2220 fgh may be generated. As ameasure to enable accountability for the accuracy of the translation(s)that are so performed, the job flow definition 2220 fgh may be generatedto additionally include the job flow identifier 2221 fgh-s thatidentifies the job flow definition 2220 fgh-s. Additionally, it may bethat the job flow definition 2220 fgh-s is maintained in a federatedarea 2566 along with the job flow definition 2220 fgh.

Turning for FIG. 16H, a new job flow that employs neuromorphicprocessing (i.e., uses a neural network to implement a function) may bederived from an existing job flow that does not employ neuromorphicprocessing (i.e., does not use a neural network, and instead, uses theexecution of a series of instructions to perform the function). This maybe done as an approach to creating a new job flow that is able to beperformed much more quickly (e.g., by multiple orders of magnitude) thanan existing job flow by using a neural network in the new job flow toperform one or more tasks much more quickly than may be possible throughthe non-neuromorphic processing employed in the existing job flow.However, as those skilled in the art will readily recognize, such aneural network may need to be trained, and neuromorphic processingusually requires the acceptance of some degree of inaccuracy that isusually not present in non-neuromorphic instruction-based processing inwhich each step in the performance of a function is explicitly set forthwith executable instructions.

Such training of a neural network of such a new job flow may entail theuse of a training data set that may be assembled from data inputs anddata outputs of one or more performances of an existing job flow. Such atraining data set may then be used, through backpropagation and/or otherneuromorphic training techniques, to train the neural network. Further,following such training, the degree of accuracy of the neural network inone or more performances of the new job flow may be tested by comparingdata outputs of the existing and new job flows that are derived fromidentical data inputs provided to each. Presuming that the new job flowincorporating use of the neural network is deemed to be accurate enoughto be put to use, there may still, at some later time, be an occasionwhere the functionality and/or accuracy of the new job flow and/or theneural network may be deemed to be in need of an evaluation. On such anoccasion, as an aid to ensuring accountability for the development ofthe new job flow and/or the neural network, it may be deemed desirableto provide an indication of what earlier job flow(s) and/or dataobject(s) were employed in training and/or in testing the new job flowand/or the neural network.

FIG. 16H provides a view of aspects of a example job flow 2200 jk thatemploys neuromorphic processing (i.e., employs a neural network), anexample job flow definition 2220 jk that defines the job flow 2200 jk,an example performance 2700 ajk of the job flow 2200 jk, and acorresponding example instance log 2720 ajk that documents theperformance 2700 ajk. This view is similar to the view provided by FIG.16A of aspects of the earlier discussed example job flow 2200 fgh thatdoes not employ neuromorphic processing (i.e., does not employ a neuralnetwork), the job flow definition 2220 fgh that defines the job flow2200 fgh, the example performance 2700 afg 2 h of the job flow 2200 fgh,and the example instance log 2720 afg 2 h that documents the performance2700 afg 2 h. As depicted in FIG. 16F, the job flow definition 2220 jkmay be defined to include a first task able to be performed by a taskroutine 2440 j that entails the use of neural configuration data 2371 j,and a second task able to be performed by a task routine 2440 k. Thetask performable by the task routine 2440 j may be that of using theneural network configuration data 2371 j to instantiate a neural network(not specifically shown), and the task performable by the task routine2440 k may be that of using that neural network to cause the job flow2200 jk to perform the same function as the job flow 2200 fgh.

The neural network configuration data 2371 j may define hyperparametersand/or trained parameters that define the neural network employed in thejob flow 2200 jk after it has been trained. In some embodiments, theneural network configuration data 2371 j may be deemed and/or handled asan integral part of the depicted example task routine 2440 j forpurposes of storage among one or more federated areas 2566. In suchembodiments, the executable instructions 2447 of the task routine 2440 jmay include some form of link (e.g., a pointer, identifier, etc.) thatrefers to the neural network configuration data 2371 j as part of amechanism to cause the retrieval and/or use of the neural networkconfiguration data 2371 j alongside the task routine 2440 j.Alternatively, in such embodiments, the task routine 2440 j may whollyintegrate the neural network configuration data 2371 j as a form ofdirectly embedded data structure.

However, in other embodiments, the neural network configuration data2371 j may be incorporated into and/or be otherwise treated as amid-flow data set 2370 j that may be stored among multiple data sets2330 and/or 2370 within one or more federated areas 2566, includingbeing subject to at least a subset of the same rules controlling accessthereto as are applied to any other data set 2330 and/or 2370. In suchother embodiments, the same techniques normally employed in selectingand/or specifying a data set 2330 or 2370 as an input to a task routine2440 in a performance of a job flow 2200 may be used to specify theneural network configuration data 2371 j as the mid-flow data set 2370 jserving as an input to the task routine 2440 j. In this way, the neuralnetwork defined by the configuration data 2371 j may be given at leastsome degree of protection against deletion, may be made available foruse in multiple different job flow flows (including other job flows thatmay perform further training of that neural network that yield improvedversions that may also be so stored), and/or may be documented withinone or more instance logs as having been employed in one or morecorresponding performances of job flows 2200.

It should be noted that, although the neural network configuration data2371 j is depicted and discussed herein as being designated and treatedas the depicted mid-flow data set 2370 j, this is in recognition of thepossibility that, within a job flow 2200, one task routine 2440 maygenerate, in a training process, the neural network configuration data2371 j as a mid-flow data set 2370 j for use by another task routine2440 within the same job flow 2200. By way of example, a job flow 2200may initially use the neural network configuration data 2371 j as is,but may then cease that initial use and initiate a training mode inwhich the neural network configuration data 2371 j is modified as aresult of further training in response to a condition such as a failureto meet a threshold of accuracy during that initial use. However, otherembodiments are possible in which the neural network configuration data2371 j is generated within one job flow 2200 for use by one or moreother job flows 2200, and/or is generated in an entirely differentprocess that is not implemented as a job flow 2200 made up of multipletasks that are performed by the execution of multiple task routines2440. Thus, other embodiments are possible in which the neural networkconfiguration data 2371 j may be more appropriately regarded as havingbeen generated as a result report 2770 in the performance of a job flow2200 and/or more appropriately regarded as a flow input data set 2330.

As also depicted in FIG. 16H, the job flow definition 2220 jk of theexample job flow 2200 jk may include the job flow identifier 2221 fgh asa form of link to the job flow definition 2220 fgh that defines theexample job flow 2200 fgh. Such a link to the job flow definition 2220fgh may be provided in the job flow definition 2220 jk in a situationwhere one or more performances (i.e., the example performance 2700 afg 2h) of the job flow 2200 fgh were used in training and/or in testing theneural network of the job flow 2200 jk. Alternatively or additionally,the instance log 2720 ajk that documents aspects of the exampleperformance 2700 afk of the example job flow 2200 jk may include theinstance log identifier 2721 afg 2 h as a link to the instance log 2720afg 2 h that documents the example performance 2700 afg 2 h. Such a linkto the instance log 2720 afg 2 h may be provided in the instance log2720 ajk in a situation where the performance 2700 afg 2 h was used intraining and/or in testing the neural network of the job flow 2200 jk.Through the provision of such links, the fact that the job flow 2200 fghand/or the specific performance 2700 afg 2 h was used in training and/orin testing the neural network of the job flow 2200 jk may be readilyrevealed, if at a later date, the job flow definition 2220 jk and/or theinstance log 2720 ajk are retrieved and analyzed as part of a laterevaluation of the job flow 2200 jk. In this way, some degree ofaccountability for how the neural network of the job flow 2200 jk wastrained and/or tested may be ensured should such training and/or testingneed to be scrutinized.

Returning to both FIGS. 16A and 16H, as depicted, either or both of theexample job flow definitions 2220 fgh or 2220 jk may additionallyinclude GUI instructions 2229 fgh or 2229 jk, respectively. Aspreviously discussed, such GUI instructions 2229 incorporated into a jobflow definition 2220 may provide instructions for execution by aprocessor to provide a job flow GUI during a performance of thecorresponding job flow 2200. As earlier discussed, a job flow definition2220 may include flow task identifiers 2241 that identify the tasks tobe performed, but not particular task routines 2440 to perform thosetasks, as a mechanism to enable the most current versions of taskroutines 2440 to be used to perform the tasks. As also earlierdiscussed, a job flow definition 2220 may also define data interfaces2223 in a way that specifies characteristics of the inputs and/oroutputs for each task to be performed, but may not specify anyparticular data object 2330 as an approach to allowing data objects 2330that are to be used as inputs to a performance to be specified at thetime a performance is to begin. Through execution of GUI instructions2229, a job flow GUI may be provided that guides a user through anopportunity to specify one or more of the data objects 2330 that are tobe used as inputs. Alternatively or additionally, a job flow GUI may beprovided to afford a user an opportunity to specify the use of one ormore particular task routines 2440 as part of an effort to analyze theaccuracy and/or other aspects of a performance of a job flow 2200. Byway of example, the GUI instructions 2229 jk, when executed, may providea user an opportunity to specify the mid-flow data set 2370 j or anotherdata object 2330, 2370 or 2770 as the one that should be used to providethe neural network configuration data 2371 j to be used to instantiatethe neural network to be used in a performance of the job flow 2200 jk.

Turning to FIG. 16I, in some embodiments, the interface definitions 2224within the job flow definition 2220 fgh may be derived as part of thegeneration of a DAG 2270 fgh based on comments 2448 about the interfaces2443/2444 and/or based on portions of the executable instructions 2447that implement the interfaces 2443/2444 within the task routines 2440 f,2440 g 2 and 2440 h. More specifically, it may be that the job flowdefinition 2220 fgh is at least partially generated from a parsing ofcomments 2448 and/or of portions of the executable instructions 2447descriptive of the input and/or output interfaces 2443 and/or 2444 ofone or more task routines 2440 that perform the functions of the jobflow 2200 fgh that the job flow definition 2220 fgh is to define. Insome embodiments, and as depicted, information concerning input toand/or output interfaces 2443 and/or 2444 from each of the task routines2440 f, 2440 g 2 and 2440 h may be stored, at least temporarily, asmacros 2470 f, 2470 g 2 and 2470 h, respectively, although it should benoted that other forms of intermediate data structure may be used inproviding intermediate storage of information concerning inputs and/oroutputs. With all of such data structures having been generated, theinformation within each that concerns input and/or output interfaces2443 and/or 2444 may then be used to generate the DAG 2270 fgh toinclude the interface definitions 2224. And it may be that, from theinterface definitions 2224, at least a portion of the flow definition2222 is able to be derived.

FIGS. 17A, 17B, 17C, 17D and 17E, together, illustrate the manner inwhich the one or more federated devices 2500 may selectively store andorganize objects within one or more federated areas 2566. FIGS. 17A-B,together, illustrate aspects of the selective translation and storage ofobjects received from one or more of the source devices 2100, or fromone or more reviewing devices 2800, within the one or more federatedareas 2566. FIGS. 17C-E, together, illustrate aspects of assigningidentifiers to objects stored within the one or more federated areas2566.

Turning to FIG. 17A, as previously discussed, the one or more federateddevices 2500 may receive objects (e.g., job flow definitions 2220, DAGs2270, flow input data sets 2330, mid-flow data sets 2370, task routines2440, macros 2470, instance logs 2720 and/or result reports 2770) fromother devices 2100 and/or 2800 as part of an exchange of objects inresponse to a request to perform any of a variety of operations. Again,in executing the portal component 2549, the processor(s) 2550 of the oneor more federated devices 2500 may be caused to operate one or more ofthe network interfaces 2590 to provide a portal accessible by otherdevices via the network 2999, and through which access may be granted bythe processor(s) 2550 to the one or more federated areas 2566. Alsoagain, any of a variety of network and/or other protocols may be used.

Alternatively, and as also previously discussed, the one or morefederated devices 2500 may receive objects as a result of an ongoingsynchronization relationship instantiated between a transfer area 2666within a federated area 2566 and another transfer area 2166 or 2866within a storage 2160 or 2860, respectively. The processor(s) 2550 ofthe one or more federated devices 2500 may be caused by the federatedarea component 2546 to refer to the federated area parameters 2536 forparameters in instantiating the transfer area 2666 within a federatedarea 2566, such as minimum and/or maximum size of the transfer area 2666and/or minimum or maximum percentage of the space within a federatedarea 2566 that is to be occupied by the transfer area 2666. Otherparameters that may be retrieved from the federated area parameters 2536may be specifications of one or more types of cooperation that may beused with the other device 2100 or 2800 with which a synchronizationrelationship is instantiated, such as whether the earlier describedpolling or volunteering approaches are to be used, and/or at whatminimum and/or maximum interval of time is to be allowed to elapsebetween each instance of exchange of status of objects within transferareas. Other parameters that may be so retrieved may includespecifications of a minimum or maximum quantity of objects to beexchanged when a transfer between transfer areas occurs.

Still another parameter concerning exchanges of objects between atransfer area 2666 within a federated area 2566 and a transfer area 2166or 2866 within a storage 2160 or 2860, respectively, that may beretrieved from the federated area parameters 2536 may be a specificationfor what minimum conditions must be met for such an automated transferof objects to be triggered. In some embodiments, the trigger may be oneor more of a minimum degree of change in an object (e.g., a minimumpercent change in size of a data object or a minimum extent of change inexecutable instructions of a task routine 2440), and/or a minimum numberof objects that must be involved in a change in status. Alternatively oradditionally, in other embodiments, the trigger for such an automatedtransfer may be a maximum amount of time to allow to elapse until thenext exchange of object(s) since the detection of a change in status ofany object.

Alternatively or additionally, and by way of example in still otherembodiments, the trigger may be associated with occurrences of objectsbeing “checked in” and/or “committed” in a formalized source codemanagement system. More specifically, and as will be familiar to thoseskilled in the art, where multiple developers are collaborating todevelop programming code for an analysis or other type of executableprogram, a source code management system may be put into place toimprove coordination thereamong. Such a source code management systemmay enforce some degree of control over which developer and/or how manydevelopers may be work with each one of different portions of executableinstructions at the same time as a proactive measure to avoid havingdifferent developers making conflicting changes to the same portion ofexecutable instructions. A developer may be required to “check out” aportion of executable instructions from the source control managementsystem to be allowed to make changes thereto, and this may serve tocause other developers to be prevented from also checking out that sameportion until the developer to which that portion is check outsubsequently “checks in” that same portion. Alternatively oradditionally, such a source code management system may track the changesmade to different portions of executable instructions by differentdevelopers as a way to provide the ability to roll back changes made byany one developer to a portion of executable instructions that is foundto “break” the ability to compile and/or interpret the executableinstructions of the analysis or other routine. There may be a compilingof the executable instructions of the analysis or other routine on arecurring interval of time which may be used as a mechanism to identifychanged portions of executable instructions that at least do not breakthe compiling of the full set of executable instructions such that theyare deemed acceptable to remain as part of the full set of executableinstructions such that those changes are deemed to be “committed”changes to the full set of executable instructions.

It may be that a portion of the storage 2160 of a source device 2100 ora portion the storage 2860 of a reviewing device 2800 is employed as thestorage at which a source code management system maintains a copy of allof the executable instructions of an analysis routine or other routineunder development by multiple developers who do not use the one or morefederated area(s) 2566 maintained by the one or more federated devices2500. Such developers may not have been granted access to a federatedarea 2566 and/or they may not be familiar with the use of federatedareas 2566. Meanwhile, there may also be other developers also involvedin developing the same analysis or other routine who do have access toand/or are familiar with the one or more federated areas 2566 maintainedby the one or more federated devices 2500. Such other developers may atleast partly rely on the enforcement of rules for the storage of objectsin federated areas 2566 as a mechanism to similarly instill a degree oforder in their collaboration among themselves in developing portions ofthe analysis or other routine. Thus, in this example embodiment, theremay be two different sets of developers collaborating on the developmentof the same analysis or other routine who are using two separate systemsof source code management to aid in coordinating their efforts.

As part of enabling collaboration between these two different groups ofdevelopers, as well as their differing systems of source codemanagement, the portion of the storage 2160 or 2860 of the device 2100or 2800 within which the source code management system maintains a copyof all of the executable instructions may be additionally designated asa transfer area 2166 or 2866, respectively. Correspondingly, at least aportion of a federated area 2566 that has been designated as thelocation in which portions of the executable instructions of theanalysis or other routine may also be stored may similarly be designatedas a transfer area 2666, and a synchronization relationship may beinstantiated between the transfer area 2666 and the other transfer area2166 or 2866. With these transfer areas and their synchronizationrelationship having been instantiated, it may be that the processor(s)2550 of the one or more federated devices 2500 are caused to cooperatewith the processor(s) 2150 of the device 2100 in which the transfer area2166 is instantiated or the processor(s) of the device 2800 in which thetransfer area 2866 is instantiated to use instances in which changes toportions of executable instructions have been “committed” or at least“checked in” as a trigger to cause the transfer of the affectedobject(s) (e.g., job flow definitions 2220 and/or task routines 2440that contain the changed executable instructions) between the transferarea 2666 and the other transfer area 2166 or 2866, respectively. Inthis way, collaboration among these two different groups of developersmay be enabled through collaboration between the systems that eachrelies upon to coordinate their development efforts in this exampleembodiment.

As also previously discussed, the processor(s) 2550 of the one or morefederated devices 2500 may selectively allow or disallow each receivedrequest (including a requests to instantiate a synchronizationrelationship) based on determinations of whether each of those requestsis authorized. Again, and more precisely, the processor(s) 2550 of theone or more federated devices 2500 may be caused by the portal component2549 to restrict what persons, devices and/or entities are to be givenaccess to one or more federated areas 2566. It should be noted that, inalternate embodiments, such control over whether access is granted maybe exerted by another device (not shown) that may be interposed betweenthe one or more federated devices 2500 and the network 2999 to serve asa gateway that controls access to the one or more federated devices2500, and thereby, controls access to the one or more federated areas.

Beyond selective granting of access to the one or more federated areas2566 (in embodiments in which the one or more federated devices 2500control access thereto), the processor(s) 2550 may be further caused byexecution of the portal component 2549 to restrict the types of accessgranted, depending on the identity of the user to which access has beengranted. Again, the portal data 2539 may indicate that different personsand/or different devices associated with a particular scholastic,governmental or business entity are each to be allowed different degreesand/or different types of access. One such person or device may begranted access to retrieve objects from within a federated area 2566,but may not be granted access to alter or delete objects, while anotherparticular person operating a particular device may be granted a greaterdegree of access that allows such actions. In embodiments in which thereis a per-object control of access, the one or more federated devices2500 (or the one or more other devices that separately control access)may cooperate with the one or more storage devices 2600 (if present) toeffect such per-object access control.

Regardless of the exact manner in which objects may be received by theone or more federated devices from other devices, and as also previouslydiscussed, the processor(s) 2550 of the one or more federated devices2500 may be caused by the admission component 2542 to impose variousrestrictions on what objects may be stored within a federated area 2566,presuming that the processor(s) 2550 have been caused by the portalcomponent 2549 to grant access in response to the received request tostore objects. Some of such restrictions may be based on dependenciesbetween objects and may advantageously automate the prevention ofsituations in which one object stored in a federated area 2566 isrendered nonfunctional as a result of another object having not beenstored within the same federated area 2566 or within a federated area2566 that is related through an inheritance relationship such that it isunavailable.

By way of example, and as previously explained, such objects as job flowdefinitions 2220 include references to tasks to be performed. In someembodiments, it may be deemed desirable to prevent a situation in whichthere is a job flow definition 2220 stored within a federated area 2566that describes a job flow that cannot be performed as a result of therebeing no task routines 2440 stored within the same federated area 2566and/or within a related federated area 2566 that are able to perform oneor more of the tasks specified in the job flow definition 2220. Thus,where a request is received to store a job flow definition 2220, theprocessor(s) 2550 may be caused by the admission component 2542 to firstdetermine whether there is at least one task routine 2440 stored withinthe same federated area 2566 and/or within a related federated area 2566to perform each task specified in the job flow definition. If thereisn't, then the processor(s) 2550 may be caused by the admissioncomponent 2542 to disallow storage of that job flow definition 2220within that federated area 2566, at least until such missing taskroutine(s) 2440 have been stored therein and/or within a relatedfederated area 2566 from which they would be accessible through aninheritance relationship. In so doing, and as an approach to improvingease of use, the processor(s) 2550 may be caused to transmit anindication of the reason for the refusal to inform an operator of thesource device 2100 of what can be done to remedy the situation.

Also by way of example, and as previously explained, such objects asinstance logs 2720 include references to such other objects as a jobflow definition, task routines executed to perform tasks, and dataobjects employed as inputs and/or generated as outputs. In someembodiments, it may also be deemed desirable to avoid a situation inwhich there is an instance log 2720 stored within a federated area 2566that describes a performance of a job flow that cannot be repeated as aresult of the job flow definition 2220, one of the task routines 2440,or one of the data objects referred to in the instance log 2720 notbeing stored within the same federated area 2566 and/or within a relatedfederated area 2566 from which they would also be accessible. Such asituation may entirely prevent a review of a performance of a job flow.Thus, where a request is received to store an instance log 2720, theprocessor(s) 2550 of the one or more federated devices 2500 may becaused by the admission component 2542 to first determine whether all ofthe objects referred to in the instance log 2720 are stored within thesame federated area 2566 and/or a related federated area 2566 in whichthey would also be accessible, thereby enabling a repeat performanceusing all of the objects referred to in the instance log 2720. If thereisn't then the processor(s) 2550 may be caused by the admissioncomponent 2542 to disallow storage of that instance log 2720 within thatfederated area 2566, at least until such missing object(s) have beenstored therein and/or within a related federated area 2566. Again, as anapproach to improving ease of use, the processor(s) 2550 may be causedto transmit an indication of the reason for the refusal to inform anoperator of the source device 2100 of what can be done to remedy thesituation, including identifying the missing objects.

Additionally by way of example, and as previously explained, suchobjects as job flow definitions 2220 may specify various aspects ofinterfaces among task routines, and/or between task routines and dataobjects. In some embodiments, it may be deemed desirable to prevent asituation in which the specification in a job flow definition 2220 of aninterface for any task routine that may be selected to perform aspecific task does not match the manner in which that interface isimplemented in a task routine 2440 that may be selected for execution toperform that task. Thus, where a request is received to store acombination of objects that includes both a job flow definition 2220 andone or more associated task routines 2440, the processor(s) 2550 may becaused to compare the specifications of interfaces within the job flowdefinition 2220 to the implementations of those interfaces within theassociated task routines 2440 to determine whether they sufficientlymatch. Alternatively or additionally, the processor(s) 2550 may becaused to perform such comparisons between the job flow definition 2220that is requested to be stored and one or more task routines 2440already stored within one or more federated areas 2566, and/or toperform such comparisons between each of the task routines 2440 that arerequested to be stored and one or more job flow definitions 2220 alreadystored within one or more federated areas 2566. If the processor(s) 2550determine that there is an insufficient match, then the processor(s)2550 may be caused to disallow storage of the job flow definition 2220and/or of the one or more associated task routines 2440. In so doing,and as an approach to improving ease of use, the processor(s) 2550 maybe caused to transmit an indication of the reason for the refusal toinform an operator of the source device 2100 of what can be done toremedy the situation, including providing details of the insufficiencyof the match.

As previously discussed, macros 2470 and DAGs 2270 may be generated frominformation concerning the inputs and/or outputs of one or more taskroutines 2440 such that, like a job flow definition 2200 and/or aninstance log 2720, each macro 2470 and each DAG 2270 is associated withone or more task routines 2440. As a result of such associations, it maybe deemed desirable to ensure that further analysis of the informationwithin each macro 2470 and/or DAG 2270 is enabled by requiring that theone or more task routines 2440 from which each is derived be availablewithin a federated area 2566 to be accessed. More specifically, inexecuting the admission component 2542, the processor(s) 2550 of the oneor more federated devices 2500 may be caused to impose restrictions onthe storage of macros 2470 and/or DAGs 2270 that may be similar to thosejust discussed for the storage of job flow definitions 2200 and/orinstance logs 2720. Thus, in response to a request to store one or moremacros 2470 and/or one or more DAGs 2270, the processor(s) 2550 mayfirst be caused to determine whether the task routine(s) 2440 on whichthe information concerning inputs and/or outputs within each macro 2470and/or within each DAG 2270 may be based is stored within a federatedarea 2566 or is provided for storage along with each 2470 and/or eachDAG 2270 for storage. Storage of a macro 2470 or of a DAG 2270 may berefused if such associated task routine(s) 2440 are not already sostored and are also not provided along with the macro 2470 or DAG 2270that is requested to be stored.

Regardless of the exact manner in which a transfer of objects betweendevices and through the network 2999 is caused to occur, it should benoted that, depending on whether grids or other groups of devices are oneither end of the transfer, some degree of parallelism may be employedin carrying out the transfer. More specifically, at least where anobject is being transferred to or transferred from multiple ones of thefederated devices 2500 (e.g., a grid 2005 of the federated devices 2500)as a result of a federated area 2566 being maintained in a distributedmanner by multiple federated devices 2500, the transfer of the singleobject may be broken up into separate and at least partially paralleltransfers of different portions of the object to or from the multiplefederated devices 2500. This may be deemed desirable for the transfer oflarger objects, such as data objects (e.g., an flow input data set 2330or a result report 2770) that may be quite large in size. Further, inembodiments in which grids of devices are involved in both ends of atransfer of an object, it may be that the transfer is performed asmultiple transfers of portions of the object in which each such portionis transferred between a different pair of devices More precisely and byway of example, where a source device 2100 that transmitted a request tostore an object in a federated area 2566 is operated as part of a gridof the source devices 2100, the granting of access to store an object inthe federated area 2566 may result in each of multiple source devices2100 transmitting a different portion of the object to a different oneof multiple federated devices 2500 in at least partially paralleltransfers.

Turning to FIG. 17B, regardless of the exact manner in which the one ormore federated devices 2500 are caused to receive objects, and aspreviously discussed, it may be that some received objects includeportions that are written in one or more secondary programminglanguages, instead of in the primary programming language normallyutilized by the processor(s) 2550 during a performance of a job flow.More specifically, among the received objects may be task routines 2440in which at least executable instructions for the performance of a taskmay be written in a secondary programming language, and/or job flowdefinitions 2220 in which at least portion(s) thereof that define inputand/or output interfaces may be written in a secondary programminglanguage. As has been previously discussed, task routines 2440 thatinclude such portions written in a secondary programming language may bestored unchanged within federated area(s), and their executableinstructions may later be interpreted and/or compiled by an appropriateruntime interpreter or compiler at the time of their execution.

However, and as also previously discussed, where a job flow definition2220 s is received that includes at least input and/or output interfacedefinitions written in a secondary programming language, it may bedeemed desirable to generate a translated form 2220 p thereof in whichthose definitions are written in the primary programming language, andto store that translated form 2220 p within a federated area in lieu ofthe originally received form 2220 s. Again, this may be done to providedevelopers who are familiar with the primary programming language with aform of the job flow definition 2220 s that is written in the primaryprogramming language to improved the ease with which they are able toread and/or edit the job flow that is defined therein.

As previously discussed, in some embodiments, as part of performingvarious comparisons of definitions for and/or implementations of inputand/or output interfaces, the processor(s) 2550 of the one or morefederated devices 2500 may be caused by the admission component 2542 totranslate each portion of each job flow definition 2220 that definesinput and/or output interfaces, and each portion of executableinstructions of each task routine that implements input and/or outputinterfaces, into an intermediate representation, such as an intermediateprogramming language or a data structure. Thus, upon receipt of thedepicted job flow definition 2220 s, the portion(s) thereof that defineinput and/or output interfaces using a secondary programming languagemay already be translated into an intermediate representation forpurposes of making such comparisons. In such embodiments, theprocessor(s) may be further caused by the interpretation component 2547to further translate that intermediate representation into the primaryprogramming language as part of generating the corresponding inputand/or output interface definitions for the job flow definition 2220 pthat is generated as the translated form of the originally received jobflow definition 2220 s.

In so doing, the processor(s) 2550 of the one or more federated devices2500 may be caused by the interpretation component 2547 to retrievevarious rules and/or other parameters for the performance of suchtranslations from the interpretation rules 2537. Among such rules and/orparameters may be a data structure providing a cross-reference of itemsof vocabulary between the primary programming language and each of oneor more secondary programming languages, and/or a data structureproviding a cross-reference of items of syntax therebetween (e.g.,punctuation, use of spacing, ordering of commands and/or data, etc.).Alternatively or additionally, among such rules and/or parameters may bea specification of the manner in which the organization of data withindata objects that is to be used in either defining input and/or outputinterfaces in job flow definitions or implementing input and/or outputinterfaces in task routines.

Turning to FIG. 17C, as depicted, the control routine 2540 may includean identifier component 2541 to cause the processor(s) 2550 of the oneor more federated devices 2500 to assign identifiers to objects storedwithin the one or more federated areas 2566. As previously discussed,each instance log 2720 may refer to objects associated with aperformance of a job flow (e.g., a job flow definition 2220, taskroutines 2440, and/or data objects used as inputs and/or generated asoutputs, such as the data sets 2330 and/or 2370, and/or a result report2770) by identifiers assigned to each. Also, as will shortly beexplained, the assigned identifiers may be employed as part of anindexing system in one or more data structures and/or databases to moreefficiently retrieve such objects. In some embodiments, the processor(s)2550 of the one or more federated devices 2500 may be caused by theidentifier component 2541 to assign identifiers to objects as they areareceived via the network 2999 from other devices, such as the one ormore source devices 2100 and/or the one or more reviewing devices 2800.In other embodiments, the processor(s) 2550 may be caused by theidentifier component 2541 to assign identifiers to objects generated asa result of a performance of a job flow (e.g., a mid-flow data set 2370or a result report 2770 generated as an output data object of a taskroutine).

In some embodiments, each identifier may be generated by taking a hashof at least a portion of its associated object to generate a hash valuethat becomes the identifier. More specifically, a job flow identifier2221 may be generated by taking a hash of at least a portion of thecorresponding job flow definition 2220; a data object identifier 2331may be generated by taking a hash of at least a portion of thecorresponding data set 2330 or 2370; a task routine identifier 2441 maybe generated by taking a hash of at least a portion of the correspondingtask routine 2440; and/or a result report identifier 2771 may begenerated by taking a hash of at least a portion of the correspondingresult report 2770. Any of a variety of hash algorithms familiar tothose skilled in the art may be employed. Such an approach to generatingidentifiers may be deemed desirable as it may provide a relativelysimple mechanism to generate identifiers that are highly likely to beunique to each object, presuming that a large enough portion of eachobject is used as the basis for each hash taken and/or each of theidentifiers is of a large enough bit width. In some embodiments, thesize of the portions of each of these different objects of which a hashis taken may be identical. Alternatively or additionally, the bit widthsof the resulting hash values that become the identifiers 2221, 2331,2441 and 2771 may be identical.

Such an approach to generating identifiers may advantageously be easilyimplemented by devices other than the one or more federated devices 2500to reliably generate identifiers for objects that are identical to theidentifiers generated by the processor(s) 2550 of any of the one or morefederated devices 2500. Thus, if a job flow is performed by anotherdevice, the instance log 2720 generated by the other device would useidentifiers to refer to the objects associated with that performancethat would be identical to the identifiers that would have beengenerated by the processor(s) 2550 of the one or more federated devices2500 to refer to those same objects. As a result, such an instance log2720 could be received by the one or more federated devices 2500 andstored within a federated area 2566 without the need to derive newidentifiers to replace those already included within that instance log2720 to refer to objects associated with a performance of a job flow.

Referring to FIG. 17A in addition to FIG. 17C, in some embodiments, theidentifier component 2541 may cooperate with the admission component2542 in causing the processor(s) 2550 of the one or more federateddevices 2500 to analyze received objects to determine compliance withvarious restrictions as part of determining whether to allow thoseobjects to be stored within the one or more federated areas 2566. Morespecifically, and by way of example, the identifier component 2541 maygenerate identifiers for each received object. The provision ofidentifiers for each received object may enable the admission component2542 to cause the processor(s) 2550 to check whether the objectsspecified in a received instance log 2720 are available among the otherobjects received along with the received instance log 2720, as well aswhether the objects specified in the received instance log 2720 areavailable as already stored within one or more of the federated areas2566. If an object referred to in the received instance log 2720 isneither among the other received objects or among the objects alreadystored within one or more of the federated area 2566, then theprocessor(s) 2550 may be caused by the admission component 2542 todisallow storage of the received instance log 2720 within the one ormore federated areas 2566. As previously discussed, disallowing thestorage of an instance log 2720 for such reasons may be deemed desirableto prevent storage of an instance log 2720 that describes a performanceof a job flow that cannot be repeated due to one or more of the objectsassociated with that performance being missing.

Turning to FIG. 17D, in some embodiments, the generation of identifiersfor instance logs 2720 may differ from the generation of identifiers forother objects. More specifically, while the identifiers 2221, 2331, 2441and 2771 may each be derived by taking a hash of at least a portion ofits corresponding object, an instance log identifier 2721 for aninstance log 2720 may be derived from at least a portion of each of theidentifiers for the objects that are associated with the performancethat corresponds to that instance log 2720. Thus, as depicted, theprocessor(s) 2550 of the one or more federated devices 2500 may becaused by the identifier component 2541 to generate an instance logidentifier 2721 for a performance of a job flow by concatenating atleast a portion of each of a job flow identifier 2221, one or more dataobject identifiers 2331, one or more task routine identifiers 2441, anda result report identifier 2771 for a job flow definition 2220, one ormore data sets 2330 and/or 2370, one or more task routines 2440, and aresult report 2770, respectively, that are all associated with thatperformance of that job flow. In embodiments in which the bit widths ofeach of the identifiers 2221, 2331, 2441 and 2771 are identical, logidentifiers 2721 may be formed from identically sized portions of eachof such identifiers 2221, 2331, 2441 and 2771, regardless of thequantity of each of the identifiers 2221, 2331, 2441 and 2771 used. Suchuse of identically sized portions of such identifiers 2221, 2331, 2441and 2771 may be deemed desirable to aid in limiting the overall bitwidths of the resulting log identifiers 2721.

FIG. 17E illustrates such a concatenation of identifiers in greaterdetail using identifiers of objects associated with the example job flow2200 fgh and the example performance 2700 afg 2 h earlier discussed inconnection with FIGS. 16A-D. As depicted, after having generated a jobflow identifier 2221 fgh, a data set identifier 2331 a, a task routineidentifier 2441 f, a task routine identifier 2441 g 2, a task routineidentifier 2441 h and a result report identifier 2771 afg 2 h for theexample job flow definition 2220 fgh, the data set 2330 a, the taskroutine 2440 f, the task routine 2440 g 2, the task routine 2440 h andthe result report 2770 afg 2 h, respectively, the processor(s) 2550 maybe caused by the identifier component 2541 to concatenate at least anidentically sized portion of each of these identifiers together to formthe single instance log identifier 2721 afg 2 h for the example instancelog 2720 afg 2 h of FIGS. 16A-D.

FIGS. 18A, 18B, 18C, 18D, 18E and 18F, together, illustrate aspects oforganizing objects within federated areas to better enable the retrievalof objects for use. FIG. 18A depicts aspects of organizing objects intodatabases within federated areas 2566. FIG. 18B depicts aspects of asingle global index that covers all federated areas 2566 within theexample hierarchical tree earlier introduced in FIGS. 15B-C, and FIG.18C depicts aspects of multiple side-by-side indexes for each privatefederated area 2566 within the same example hierarchical tree. FIG. 18Dillustrates aspects of selective retrieval of objects from one or morefederated areas 2566 in response to requests received from one or moreof the reviewing devices 2800, and FIG. 18E illustrates aspects of theuse of identifiers assigned to objects to locate objects within one ormore federated areas 2566 and/or to identify object associations. FIG.18F illustrates aspects of the retrieval of a job flow definition inwhich a translation is performed between programming languages.

Turning to FIG. 18A, as depicted, the control routine 2540 may include adatabase component 2545 to cause the processor(s) 2550 of the one ormore federated devices 2500 to organize various ones of the objects2220, 2270, 2330, 2370, 2440, 2470, 2720 and 2770 into one or moredatabases 2562, 2563, 2564 and/or 2567 (or one or more of another typeof data structure) for more efficient storage and retrieval thereofwithin the one or more federated areas 2566. In some embodiments inwhich there are multiple unrelated federated areas 2566, theprocessor(s) 2566 may be caused to instantiate a separate instance ofeach of the databases 2562, 2563, 2564 and/or 2567 within each of thoseunrelated federated areas 2566. In other embodiments in which there aremultiple federated areas 2566 that are related to each other as by beingincluded in either a single linear hierarchy (e.g., the example linearhierarchy introduced in FIG. 15A) or a single hierarchical tree (e.g.,the example hierarchical tree introduced in FIGS. 15B-C), theprocessor(s) 2566 may be caused to instantiate a single instance of eachof the databases 2562, 2563, 2564 and/or 2567 that may cover all ofthose multiple related federated areas 2566. However, in still otherembodiments in which there are multiple federated areas 2566 that arerelated to each other as by being included in a single hierarchicaltree, the processor(s) 2566 may be caused to instantiate multipleinstances of each of the databases 2562, 2563, 2564 and/or 2567, whereeach of those multiple instances covers a different subset of thosemultiple related federated areas 2566 that exists within a different oneof the branches of the hierarchical tree. Still other embodiments arepossible in which each instance of each of the databases 2562, 2563,2564 and/or 2567 may cover one or multiple related and/or unrelatedfederated areas 2566.

Within each instance of the job flow database 2562, the job flowdefinitions 2220 may be indexed or made otherwise addressable by theircorresponding job flow identifiers 2221. In some embodiments, DAGs 2270may be stored within each instance of the job flow database(s) 2562alongside the job flow definitions 2220. As has been discussed, new jobflow definitions 2220 may be at least partially based on DAGs 2270.

Within each instance of the data object database 2563, the data sets2330 and/or 2370 may be accessible via their corresponding data objectidentifiers 2331, and/or each of the result reports 2770 may beaccessible via their corresponding result report identifiers 2771.

Within each instance of the task routine database 2564, the taskroutines 2440 may be indexed or made otherwise addressable both by theircorresponding task routine identifiers 2441, and by the flow taskidentifiers 2241 that each may also be assigned to indicate theparticular task that each is able to perform. As has been discussed,there may be tasks that multiple task routines 2440 are able to performsuch that there may be sets of multiple task routines 2440 that allshare the same flow task identifier 2241. In some embodiments, a searchof an instance of the task routine database 2564 using a flow taskidentifier 2241 to find a task routine 2440 that is able to perform thecorresponding task may beget an indication from that instance of thetask routine database 2564 of there being more than one of such taskroutines 2440, such as a list of the task routine identifiers 2441 ofsuch task routines 2440. Such an indication may also include anindication of which of the multiple task routines 2440 so identified isthe most recent version thereof. Such an indication may be provided byan ordering of the task routine identifiers 2441 of the multiple taskroutines 2440 that places the task routine identifier 2441 of the mostrecent version of the task routines 2440 at a particular position withinthe list. In this way, indications of whether one or multiple taskroutines 2440 exists that are able to perform a task, as well as whichone of multiple task routines 2440 is the newest version, may be quicklyprovided from an instance of the task routine database 2564 in a mannerthat obviates the need to access and/or analyze any of the task routines2440 therefrom.

In some embodiments, macros 2470 may be stored within each instance ofthe task routine database(s) 2564 alongside the task routines 2440 fromwhich each macro 2470 may be derived. As will be explained in greaterdetail, it may be deemed desirable to enable each macro 2470 to besearchable based on either the task routine identifier 2441 of thespecific task routine 2440 from which it was generated, or the flow taskidentifier 2241 of the task that the task routine 2440 performs.

Within each instance of the instance log database 2567, the instancelogs 2720 may be indexed or made otherwise addressable by theircorresponding instance log identifiers 2721. As has been discussed, eachperformance of a job flow may cause the generation of a separatecorresponding instance log 2720 during that performance that provides alog of events occurring during the performance, including and notlimited to, each performance of a task. In such embodiments, eachinstance log 2720 may be implemented as a separate data structure and/orfile to provide indications of events occurring during the performanceto which it corresponds. However, other embodiments are possible inwhich each of the instance logs 2720 is implemented as an entry of alarger log data structure and/or larger log data file, such as aninstance of the instance log database 2567. In some embodiments, themanner in which the instance log identifiers 2721 of the instance logs2720 are stored within an instance of the instance log database 2567 (orother data structure) may be structured to allow each of the instancelog identifiers 2721 to be searched for at least portions of particularidentifiers for other objects that were concatenated to form one or moreof the instance log identifiers 2721. As will shortly be explained ingreater detail, enabling such searches to be performed of the instancelog identifiers 2721 may advantageously allow an instance log 2720 for aparticular performance of a particular job flow to be identified in amanner that obviates the need to access and/or analyze any of theinstance logs 2720 within an instance log database 2567.

As depicted, in embodiments in which there are multiple relatedfederated areas, and a single instance of each of the databases 2562,2563, 2564 and/or 2567 has been instantiated to cover those multiplefederated areas, each of the object identifiers 2221, 2331, 2441, 2721and/or 2771 may be accompanied by a corresponding object locationidentifier 2222, 2332, 2442, 2722 and/or 2772, respectively, that servesto identify which federated area 2566 of the multiple related federatedareas 2566 that the corresponding object may be stored within. Thus, andmore precisely, each job flow identifier 2221 may be accompanied by ajob flow location identifier 2222 that serves to identify which ofmultiple related federated areas 2566 the corresponding job flowdefinition 2220 or DAG 2270 is stored within. Similarly, each dataobject identifier 2331 may be accompanied by a data object locationidentifier 2332 that serves to identify which of multiple relatedfederated areas 2566 the corresponding data set 2330 or 2370 is storedwithin. Similarly, each result report identifier 2771 may be accompaniedby a result report location identifier 2772 that serves to identifywhich of multiple related federated areas 2566 the corresponding resultreport 2770 is stored within. Similarly, each task routine identifier2441 may be accompanied by a task routine location identifier 2442 thatserves to identify which of multiple related federated areas 2566 thecorresponding task routine 2440 or macro 2470 is stored within.Similarly, each instance log identifier 2721 may be accompanied by aninstance log location identifier 2722 that serves to identify which ofmultiple related federated areas 2566 the corresponding instance log2720 is stored within.

FIG. 18B depicts the resulting hierarchy-wide coverage of the resultingsingle set of object identifiers 2221, 2331, 2441, 2771 and/or 2721, andobject location identifiers 2222, 2332, 2442, 2772 and/or 2722,respectively, in embodiments in which a single instance of each of thedatabases 2562, 2563, 2564 and/or 2567 covers all of the multiplefederated areas 2566 within a single set of related federated areaswithin a single hierarchical structure, such as the depicted examplehierarchical tree introduced in FIGS. 15B-C. Thus, the single depictedset of object identifiers and object location identifiers may be used inretrieving any of the corresponding types of objects that may be storedwithin any of the federated areas 2566 m, 2566 q, 2566 r, 2566 u and2566 x of the depicted example hierarchical tree.

In contrast, FIG. 18C depicts the resulting per-branch coverage of theresulting multiple sets of object identifiers 2221 m, 2331 m, 2441 m,2771 m and/or 2721 m; 2221 q, 2331 q, 2441 q, 2771 q and/or 2721 q;and/or 2221 r, 2331 r, 2441 r, 2771 r and/or 2721 r; and object locationidentifiers 2222 m, 2332 m, 2442 m, 2772 m and/or 2722 m; 2222 q, 2332q, 2442 q, 2772 q and/or 2722 q; and/or 2222 r, 2332 r, 2442 r, 2772 rand/or 2722 r; respectively, in embodiments in which a separate instanceof each of the databases 2562, 2563, 2564 and/or 2567 covers a differentsubset of the multiple federated areas 2566 within a different branch ofa single set of related federated areas within a single hierarchicaltree. Thus, one of the depicted sets of object identifiers and objectlocation identifiers may be used in retrieving any of the correspondingtypes of objects that may be stored within either of the federated areas2566 m or 2566 x; while another of the depicted sets of objectidentifiers and object location identifiers may be used in retrievingany of the corresponding types of objects that may be stored within anyof the federated areas 2566 q, 2566 u or 2566 x; and still another ofthe depicted sets of object identifiers and object location identifiersmay be used in retrieving any of the corresponding types of objects thatmay be stored within any of the federated areas 2566 r, 2566 u or 2566x.

Turning to FIG. 18D, and as previously discussed, the one or morefederated devices 2500 may receive a request from one of the sourcedevices 2100 or one of the reviewing devices 2800 to retrieve one ormore objects associated with a job flow from within the one or morefederated areas 2566 and provide it to the requesting device 2100 or2800. Alternatively, the request may be to use one or more objectsassociated with a job flow, and retrieved from the one or more federatedareas 2566, to perform an analysis and provide the results thereof. Or,an another alterative, the request may be to use one or more objectsassociated with a job flow, and retrieved from the one or more federatedareas 2566, to repeat a past performance of that job flow and providethe results thereof and/or the results of a comparison of past and newresults thereof. In some embodiments, the processor(s) 2550 of the oneor more federated devices 2500 may be caused by the portal component2549 to queue such requests as request data 2535 to enable out-of-orderhandling of requests, and/or other approaches to increase the efficiencywith which such requests are responded to. As previously discussed, theprocessor(s) 2550 may also be caused by the portal component todetermine whether each of the received requests originated from anauthorized person, an authorized device and/or an authorized entity,and/or to determine whether the type of request is authorized fororiginating person, device and/or entity.

As depicted, the control routine 2540 may also include a selectioncomponent 2543 to employ one or more identifiers provided in a requestand/or one or more rules to locate, select and retrieve objectsassociated with a job flow from the one or more federated areas 2566. Inexecuting the selection component 2543 and the database component 2545to provide requested objects, the processor(s) 2550 may be caused to useone or more identifiers of objects that may be provided in a grantedrequest to directly retrieve those one or more objects from one or morefederated areas 2566. By way of example, a request may be received forthe retrieval and transmission to the requesting device 2100 or 2800 ofa particular data set 2330, and the request may include the data objectidentifier 2331 of the particular data set 2330. In response to therequest, the processor(s) 2550 may be caused by the database component2545 to employ the provided data object identifier 2331 (and maybe to doso along with one or more correlated data object location identifiers2332, as previously discussed) to search for the particular data set2330 within the one or more federated areas 2566, retrieve it, andtransmit it to the requesting device 2800. In so doing, the processor(s)2550 may be caused to correlate the received data object identifier 2331to a corresponding data logic location identifier 2332, and to thenretrieve the particular data object 2330 from the federated area 2566pointed to by that data logic location identifier 2332.

However, other requests may be for the retrieval of objects from one ormore federated areas 2566 where the identifiers of the requested objectsmay not be provided within the requests. Instead, such requests mayemploy other identifiers that provide an indirect reference to therequested objects.

In one example use of an indirect reference to objects, a request may bereceived for the retrieval and transmission to the requesting device2100 or 2800 of a task routine that performs a particular task, and therequest may include the flow task identifier 2241 of the particular taskinstead of any task routine identifier 2441 that directly identifies anyparticular task routine 2440. The processor(s) 2550 may be caused by theselection component 2543 and database component 2545 to employ the flowtask identifier 2241 provided in the request to search within one ormore federated areas 2566 for such task routines 2440. As has beenpreviously discussed, the search may entail correlating the flow taskidentifiers 2241 to one or more task routine identifiers 2441 of thecorresponding one or more task routines 2440 that may perform the taskidentified by the flow task identifier 2241. In embodiments in which thetask routines 2440 have been organized into a task routine database 2564within each federated area 2566 as depicted as an example in FIG. 18A(or other searchable data structure), the search may entail searcheswithin such a database or other data structure. The result of such asearch may be an indication from such a database or other data structurewithin the one or more federated areas 2566 that there is more than onetask routine 2440 that is able to perform the task identified by theflow task identifier 2241 provided in the request. As previouslydiscussed, such an indication may be in the form of a list of the taskroutine identifiers 2441 for the task routines 2440 that are able toperform the specified task. Additionally, and as also previouslydiscussed, such a list may be ordered to provide an indication of whichof those task routines 2440 stored within a federated area 2566 is thenewest. Again, it may be deemed desirable to favor the use of the newestversion of a task routine 2440 that performs a particular task wherethere is more than one task routine 2440 stored within one or morefederated areas 2566 that is able to do so. Therefore, in response tothe request, the processor(s) 2550 may be caused to select the newesttask routine 2440 indicated among all of the one or more of such listsretrieved within each of one or more federated areas 2566 to perform thetask specified in the request by the flow task identifier 2241, and totransmit that newest version to the requesting device. Through suchautomatic selection and retrieval of the newest versions of taskroutines 2440, individuals and/or entities that may be developing newanalyses may be encouraged to use the newest versions.

In another example use of an indirect reference to objects, a requestmay be received by the one or more federated devices 2500 to repeat aprevious performance of a specified job flow with one or more specifieddata objects as inputs (e.g., one or more of the data sets 2330), or toprovide the requesting device with the objects needed to repeat theprevious performance of the job flow, itself. Thus, the request mayinclude the job flow identifier 2221 of the job flow definition 2220 forthe job flow, and may include one or more data object identifiers 2331of the one or more data sets 2330 to be employed as inputs to theprevious performance of that job flow sought to be repeated, but may notinclude identifiers for any other object associated with that previousperformance.

The processor(s) 2550 may be caused by the selection component 2543 toemploy the job flow identifier 2221 and the one or more data objectsidentifiers 2331 provided in the request to search the one or morefederated areas 2566 for all instance logs 2720 that provide anindication of a past performance of the specified job flow with thespecified one or more input data objects. In embodiments in which theinstance logs 2720 have been organized into an instance log database2567 as depicted as an example in FIG. 18A (or other searchable datastructure), the search may be within such a database or other datastructure, and may be limited to the instance log identifiers 2721. Morespecifically, in embodiments in which the instance log identifiers 2721were each generated by concatenating the identifiers of objectsassociated with a corresponding past performance, the instance logidentifiers 2721, themselves, may be analyzed to determine whether theidentifiers provided in the request for particular objects are includedwithin any of the instance log identifiers 2721. Thus, the processor(s)2550 may be caused to search each instance log identifier 2721 todetermine whether there are any instance log identifiers 2721 thatinclude the job flow identifier 2221 and all of the data objectidentifiers 2331 provided in the request. If such an instance logidentifier 2721 is found, then it is an indication that the instance log2720 that was assigned that instance log identifier 2721 is associatedwith a past performance of that job flow associated with the one or moredata sets 2330 specified in the request.

It should be noted, however, that a situation may arise in which morethan one of such instance log identifiers 2721 may be found, indicatingthat there has been more than one past performance of the job flow withthe one or more data sets. In response to such a situation, theprocessor(s) 2550 may be caused by the selection component 2543 totransmit an indication of the multiple previous performances to therequesting device 2100 or 2800 along with a request for a selection tobe made from among those previous performances. The processor(s) 2550may then await a response from the requesting device 2100 or 2800 thatprovides an indication of a selection from among the multiple pastperformances. As an alternative to such an exchange with the requestingdevice 2100 or 2800, or in response to a predetermined period of timehaving elapsed since requesting a selection without an indication of aselection having been received by the one or more federated devices2500, the processor(s) 2550 may be caused by the selection component2543 to, as a default, select the most recent one of the pastperformances.

After identifying a single past performance, or after the selection ofone of multiple past performances, the processor(s) 2550 may then becaused by the selection component 2543 to retrieve the task routineidentifiers 2441 specified within the corresponding instance log 2720 ofthe particular task routines 2440 used in the previous performance. Theprocessor(s) 2550 may then be caused by the database component 2545 toemploy those task routine identifiers 2441 to retrieve the particulartask routines 2440 associated with the previous performance from one ormore federated areas 2566. The processor(s) 2550 may also be caused bythe selection component 2543 to retrieve the result report identifier2771 specified within the instance log 2720 of the result report thatwas generated in the previous performance. The processor(s) 2550 may befurther caused by the selection component 2543 to retrieve any dataobject identifiers 2331 that may be present within the instance log 2720that specify one or more data sets 2370 that may have been generated asa mechanism to exchange data between task routines 2440 during theperformance of a job flow.

If the request was for the provision of objects to the requestingdevice, then the processor(s) 2550 may be caused by the databasecomponent 2543 to retrieve, from the one or more federated areas, thejob flow definition 2220 and the one or more data sets 2330 specified bythe job flow identifier 2221 and the one or more data object identifiers2331, respectively, in the request, and may be further caused by theportal component 2549 to transmit those objects to the requesting device2100 or 2800. The processor 2550 may also be caused by the portalcomponent 2549 to transmit the instance log 2720 generated in the pastperformance, and the result report 2770 specified by the result reportidentifier 2771 retrieved from the instance log 2720. If any data sets2370 were indicated in the instance log 2720 as having been generated inthe previous performance, then the processor(s) 2550 may be furthercaused by the portal component 2549 to transmit such data set(s) 2370 tothe requesting device 2100 or 2800 after having been caused to retrievesuch data set(s) 2370 from the one or more federated areas 2566 by thedatabase component 2545. Thus, based on a request that provided onlyidentifiers for a job flow definition 2220 and one or more data objectsused as inputs to a past performance of the job flow, a full set ofobjects may be automatically selected and transmitted to the requestingdevice to enable an independent performance of the job flow as part of areview of that previous performance.

However, if the request was for a repeat of the previous performance ofthe job flow by the one or more federated devices 2500, then instead of(or in addition to) transmitting the objects needed to repeat theprevious performance to the requesting device 2100 or 2800, theprocessor(s) 2550 may be caused by execution of a performance component2544 of the control routine 2540 to use those objects to repeat theprevious performance within a federated area 2566 in which at least oneof the objects is stored and/or to which the user associated with therequest and/or the requesting device 2100 or 2800 has been grantedaccess. In some embodiments, the federated area 2566 in which theprevious performance took place may be selected, by default, to be thefederated area 2566 in which to repeat the performance. Indeed,repeating the performance within the same federated area 2566 may bedeemed a requirement to truly reproduce the conditions under which theprevious performance occurred. More specifically, the processor(s) 2550may be caused to execute the task routines 2440 specified in theinstance log 2720, in the order specified in the job flow definition2220 specified in the request, and using the one or more data sets 2330specified in the request as input data objects. In some embodiments,where multiple ones of the federated devices 2500 are operated togetheras the federated device grid 2005, the processor(s) 2550 of the multipleones of the federated devices 2500 may be caused by the performancecomponent 2544 to cooperate to divide the execution of one or more ofthe tasks thereamong. Such a division of one or more of the tasks may bedeemed desirable where one or more of the data objects associated withthe job flow is of relatively large size. Regardless of the quantity ofthe federated devices 2500 involved in repeating the previousperformance of the job flow, upon completion of the repeat performance,the processor(s) 2550 may be further caused by the performance component2544 to transmit the newly regenerated result report 2770 to therequesting device. Alternatively or additionally, the processor(s) 2550may perform a comparison between the newly regenerated result report2770 and the result report 2770 previously generated in the previousperformance to determine if there are any differences, and may transmitan indication of the results of that comparison to the requestingdevice. Thus, based on a request that provided only identifiers for ajob flow definition 2220 and one or more data objects used as inputs tothe job flow, a previous performance of a job flow may be repeated andthe results thereof transmitted to the requesting device as part of areview of the previous performance.

In still another example use of an indirect reference to objects, arequest may be received by the one or more federated devices 2500 toperform a specified job flow with one or more specified data objects asinputs (e.g., one or more of the data sets 2330). Thus, the request mayinclude the job flow identifier 2221 of the job flow definition 2220 forthe job flow, and may include one or more data object identifiers 2331of the one or more data sets 2330 to be employed as input data objects,but may not include any identifiers for any other objects needed for theperformance.

The processor(s) 2550 may be caused by the selection component 2543 toemploy the job flow identifier 2221 provided in the request to retrievethe job flow definition 2220 for the job flow to be performed. Theprocessor(s) 2550 may then be caused to retrieve the flow taskidentifiers 2241 from the job flow definition 2220 that specify thetasks to be performed, and may employ the flow task identifiers 2241 toretrieve the newest version of task routine 2440 within one or morefederated areas 2566 (e.g., within the task routine database 2564 withineach of one or more federated areas 2566) for each task. Theprocessor(s) 2550 may also be caused by the selection component 2543 toemploy the job flow identifier 2221 and the one or more data objectsidentifiers 2331 to search the one or more federated areas 2566 for anyinstance logs 2720 that provide an indication of a past performance ofthe specified job flow with the specified one or more input dataobjects.

If no such instance log identifier 2721 is found, then it is anindication that there is no record within the one or more federatedareas of any previous performance of the specified job flow with the oneor more specified data sets 2330. In response, the processor(s) 2550 maybe caused by execution of the performance component 2544 to execute theretrieved newest version of each of the task routines 2440 to performthe tasks of the job flow in the order specified in the job flowdefinition 2220 specified in the request, and using the one or more datasets 2330 specified in the request as input data objects. Again, inembodiments in which multiple ones of the federated devices 2500 areoperated together as the federated device grid 2005, the processor(s)2550 may be caused by the performance component 2544 to cooperate todivide the execution of one or more of the tasks thereamong. Uponcompletion of the performance of the job flow, the processor(s) 2550 maybe further caused by the performance component 2544 to transmit theresult report 2770 generated in the performance of the job flow to therequesting device. Thus, based on a request that provided onlyidentifiers for a job flow definition 2220 and one or more data objectsused as inputs to the job flow, a performance of a job flow is caused tooccur using the newest available versions of task routines 2440 toperform each task.

However, if such an instance log identifier 2721 is found, then it is anindication that there was a previous performance of the job flowspecified in the request where the one or more data sets 2330 specifiedin the request were used as input data objects. If a situation shouldoccur where multiple ones of such instance log identifiers 2721 arefound, then it is an indication that there have been multiple previousperformances of the job flow, and the processor(s) 2550 may be caused bythe selection component 2543 to select the most recent one of themultiple previous performances, by default. After the finding of asingle previous performance, or after the selection of the most recentone of multiple previous performances, the processor(s) 2550 may then becaused by the selection component 2543 to retrieve the task routineidentifiers 2441 specified within the corresponding instance log 2720 ofthe particular task routines 2440 used in the previous performance. Theprocessor(s) 2550 may then employ those task routine identifiers 2441 toretrieve the particular task routines 2440 associated with the previousperformance from one or more federated areas 2566. The processor 2550may then compare each of the task routines 2440 specified in theinstance log 2720 to the newest task routines 2440 retrieved for eachtask specified in the job flow definition 2220 to determine whether allof the task routines 2440 specified in the instance log 2720 are thenewest versions thereof. If so, then the result report 2770 generated inthe previous performance associated with the instance log 2720 wasgenerated using the most recent versions of each of the task routines2440 needed to perform the tasks of the job flow. The processor(s) 2550may then entirely forego performing the job flow, may employ the resultreport identifier 2771 provided in the instance log 2720 to retrieve theresult report 2770 generated in the earlier performance, and maytransmit that result report 2770 to the requesting device. In this way,a form of caching is provided by which the previously generated resultreport 2770 is able to be recognized as reusable, and the use ofprocessing resources of the one or more federated devices 2500 to repeata previous performance of the job flow is avoided.

It should be noted, however, that a situation may arise in which one ormore of the task routines 2440 specified in the instance log 2720 arethe newest versions thereof, while one or more others of the taskroutines 2440 specified in the instance log 2720 are not. In response tosuch a situation, the processor(s) 2550 may be caused by the selectionroutine 2543 to check whether at least the task routine 2440 specifiedin the instance log 2720 as performing the first task in the order oftasks specified in the job flow definition 2220 is the newest version oftask routine 2440 able to perform that task. If not, then theprocessor(s) 2550 may be caused by the performance component 2544 toemploy all of the newest versions of the task routines 2440 to performthe entire job flow, just as the processor(s) 2550 would be caused to doso if there had been no previous performance of the job flow, at all.However, if the first task in the previous performance of the job flowwas performed with the newest version of task routine 2440 able toperform that first task, then the processor(s) 2550 may iterate througheach task in the order of tasks specified in job flow definition 2720 todetermine which were performed with the newest version of task routine2440. The processor(s) 2550 would start with the first task in thespecified order of tasks, and stop wherever in the specified order oftasks the processor(s) 2550 determine that a task routine 2440 was usedthat is not the newest version thereof. In this way, the processor(s)2550 may identify an initial portion of the order of tasks specified inthe job flow definition 2220 that may not need to be performed again asthey were already performed using the newest versions of theirrespective task routines 2440. As a result, only the remainder of thetasks that follow the initial portion in the order of tasks may need tobe performed again, but using the newest versions of their respectivetask routines 2440 for all of those remaining tasks. In this way, a formof partial caching is provided by which an initial portion of a previousperformance of a job flow is able to be reused such that not all of thejob flow needs to be performed again to generate a result report 2770 tobe transmitted to the requesting device.

FIG. 18E illustrates two examples of searching for objects using one ormore identifiers that provide an indirect reference to those objects ingreater detail. More specifically, FIG. 18E depicts two differentsearches for objects that each employ the example instance logidentifier 2721 afg 2 h associated with the 2720 afg 2 h instance log ofthe example performance of the job flow 2200 fgh of FIGS. 16A-D.

In one example search, and referring to both FIGS. 18D and 18E, arequest may be received (and stored as part of the request data 2535)for the retrieval of objects associated with, and/or for a repetitionof, the example performance 2700 afg 2 h that resulted in the generationof the result report 2770 afg 2 h. In so doing, the request may use theresult report identifier 2771 afg 2 h to refer to the result report 2770afg 2 h, while providing no other identifier for any other objectassociated with the performance 2700 afg 2 h. In response, theprocessor(s) 2550 may be caused by the selection component 2543 tocooperate with the database component 2545 to search the instance logidentifiers 2721 of the instance log database 2567 within one or morefederated areas 2566 to locate the one of the multiple instance logidentifiers 2721 that includes the result report identifier 2771 afg 2h. As depicted, the instance log identifier 2721 afg 2 h is the one ofthe multiple instance log identifiers 2721 that contains the resultreport identifier 2771 afg 2 h. With the instance log identifier 2721afg 2 h having been found, the processor(s) 2550 may then be caused bythe selection component 2543 to retrieve, from the instance log 2720 afg2 h, the identifiers of the various objects requested to be transmittedto the requesting device and/or needed to repeat the example performance2700 afg 2 h.

In another example search, a request may be received for a repetition ofa previous performance of a specific job flow with a specific dataobject used as input. In so doing, the request may refer to the examplejob flow 2200 fgh of FIGS. 16A-D by using the job flow identifier 2221fgh of the job flow definition 2220 fgh that defines the example jobflow 2200 fgh, and may refer to the data set 2330 a by using the dataobject identifier 2331 a. In response, the processor(s) 2550 may becaused by the selection component 2543 to cooperate with the databasecomponent 2545 to search the instance log identifiers 2721 of theinstance log database 2567 within one or more federated areas 2566 tolocate any of the multiple instance log identifiers 2721 that includesthe both the job flow identifier 2221 fgh and the data object identifier2331 a. As depicted, the instance log identifier 2721 afg 2 h is the oneof the multiple instance log identifiers 2721 that contains both ofthese identifiers 2221 fgh and 2331 a. With the instance log identifier2721 afg 2 h having been found, the processor(s) 2550 may then be causedby the selection component 2543 to retrieve, from the instance log 2720afg 2 h, the identifiers of the various objects needed to repeat theexample performance 2700 afg 2 h. The processor(s) 2550 may then becaused by execution of the performance component 2544 to perform theexample job flow 2200 fgh with the data set 2330 a as the input dataobject.

As an alternative to the one or more federated devices 2500 transmittingobjects to another device 2100 or 2800 in response to requests, and aspreviously discussed, the one or more federated devices 2500 may,instead, transmit objects to another device 2100 or 2800 as a result ofan ongoing synchronization relationship instantiated between a transferarea 2666 within a federated area 2566 and another transfer area 2166 or2866 within a storage 2160 or 2860 of the other device 2100 or 2800,respectively. Again, the instantiation of the synchronizationrelationship may be in response to a request received by the one or morefederated devices 2500. And again, in some embodiments, such asynchronization relationship may be requested and instantiated tosupport a collaboration among developers who have access to and arefamiliar with the use of the one or more federated areas 2566 of the oneor more federated devices 2500, and developers who do not have access toand/or are not familiar with the use of those one or more federatedareas 2566.

Turning to FIG. 18F, regardless of the exact manner in which the one ormore federated devices 2500 are caused to transmit an object to anotherdevice 2100 or 2800, it may be that the other device 2100 or 2800requires a portion of the transmitted object to be written in asecondary programming language that is not utilized by the processor(s)2550 of the one or more federated devices 2500 in the performance of jobflows. In some embodiments, it may be that this requirement is to beapplied solely to job flow definitions 2220 that are to be transmittedby the one or more federated devices 2500 back to the other device 2100or 2800, as it may be that other objects may not be transmitted back tothe other device 2100 or 2800. Thus, in such embodiments, the depictedjob flow definition 2220 p, which includes input and/or output interfacedefinitions written in the primary programming language, is to betranslated into the depicted other form 2220 s, which includescorresponding input and/or output interface definitions written in thesecondary programming language.

In some of such embodiments, the processor(s) 2550 of the one or morefederated devices 2500 may be caused to perform a reverse version of thetranslation process described in connection with FIG. 17B by which thejob flow definition 2220 p stored within a federated area may have beengenerated from an earlier received version thereof in which the inputand/or output interface definitions were written in a secondarylanguage. More specifically, the processor(s) 2550 may be caused totranslate the input and/or output interface definitions within thedepicted job flow definition 2220 p into an intermediate representation,just as might normally be done to enable a comparison to input and/oroutput interface implementations by one or more task routines 2440.Subsequently, the processor(s) 2550 may be caused to translate the inputand/or output definitions from the intermediate representation and intothe secondary programming language within the depicted job flowdefinition 2220 s that is transmitted to the other device 2100 or 2800.

Alternatively, in other embodiments in which the transmission of objectsback to the other device 2100 or 2800 is limited to job flow definitions2220, and at least the input and/or output interface definitions thereofare required to be written in the secondary programming language, theprocessor(s) 2550 may be caused by the interpretation component 2547 toperform a direct translation from the at least the input and/or outputdefinitions written in the primary programming language within thedepicted job flow definition 2220 p, and into at least the input and/oroutput definitions written in the secondary programming language withinthe depicted job flow definition 2220 s that is transmitted to the otherdevice 2100 or 2800. Such a direct translation may be deemed desirablewhere a fuller translation capability is needed as a result of thedepicted job flow definition 2220 p also including GUI instructions thatneed to be translated from the primary programming language into thesecondary programming language to generate corresponding GUIinstructions within the depicted job flow definition 2220 s

As previously discussed, such a synchronized relationship in which thereis a need for translations between programming languages may beinstantiated in support of a collaboration among developers to developan analysis or other routine that includes developers with access to andan understanding of the use of the one or more federated areas 2566, andother developers who do not have access to and/or an understanding ofthe use of the one or more federated areas 2566. Again, such otherdevelopers may, instead, rely upon an implementation of a source codemanagement system within the other device 2100 or 2800.

Again, in such a situation, the synchronization relationship may entailmaintaining synchronization of contents between a transfer area 2666instantiated within a federated area 2566 maintained by the one or morefederated devices 2500 and a transfer area 2166 or 2866 maintainedwithin the storage 2160 or 2860 of the other device 2100 or 2800,respectively. Again, the transfer area 2166 or 2866 may also be theportion of the storage 2160 or 2860 of the device 2100 or 2800 withinwhich a source code management system maintains a copy of all of theexecutable instructions. Correspondingly, the transfer area 2666instantiated within a federated area 2566 may also be the designatedlocation in which portions of the executable instructions of theanalysis or other routine are to be stored as objects. With thesetransfer areas and their synchronization relationship having beeninstantiated, it may be that the processor(s) 2550 of the one or morefederated devices 2500 are caused to cooperate with the processor(s)2150 of the device 2100 in which the transfer area 2166 is instantiatedor the processor(s) of the device 2800 in which the transfer area 2866is instantiated to use instances in which changes to portions ofexecutable instructions have been “committed” or at least “checked in”as a trigger to cause the transfer of the affected object(s)therebetween.

FIGS. 19A, 19B, 19C, 19D and 19E, together, illustrate various aspectsof the generation of a DAG 2270 and the provision of a visualization2980 of a DAG 2270 in greater detail. FIG. 19A illustrates aspects ofcollecting information concerning inputs and/or outputs of at least onetask routine 2440 in preparation for generating a DAG 2270. FIG. 19Billustrates aspects of generating a DAG 2270 based on collectedinformation concerning inputs and/or outputs of at least one taskroutine 2440. FIGS. 19C and 19D, taken together, illustrate aspects ofgenerating a visualization 2980 of a DAG 2270 to visually indicate aconnection or a lack of connection between a pair of task routines. FIG.19E illustrates aspects of the generation and storage of a new DAG 2270from a visualization 2980 of an edited DAG 2270.

FIG. 19A illustrates aspects of the generation of a macro 2470 for eachtask routine 2440 that may be included in a DAG 2270 as an intermediatestep to generating the DAG 2270. Such an intermediate step may beperformed where the objects that serve as the sources of the informationto be depicted in a DAG 2270 are located remotely from where avisualization 2980 of the DAG 2270 is to be displayed, such as wherethose objects are stored within federated area(s) 2566 maintained by oneor more federated devices 2500, but the DAG 2270 is to be displayed by asource device 2100 or a reviewing device 2800. In such situations, theone or more macros 2470 that are so generated may then be transmitted tothe device that is to display the visualization 2980 to enable the DAG2270 to be generated thereat from the one or more macros 2470. However,it should be noted that, where the DAG 2270 is to be generated and/or avisualization 2980 of it is to be displayed locally (e.g., by acomputing device with more direct access to the objects that serve asthe sources of the information to be depicted), then the DAG 2270 may begenerated more directly, and while foregoing the generation of macro(s)2470. Also, as an alternative to the generation and transmission ofmacros 2470 to a remote device that is to display a DAG 2270 generatedtherefrom, the DAG 2270, itself, may be generated locally (e.g., at oneor more of the federated devices 2500) and then an image of the DAG 2270may be transmitted to the device that is to display a visualization 2980of the DAG 2270.

As depicted, an example task routine 2440 from which at least a portionof a DAG 2270 may be generated may include executable instructions 2447written in any of a variety of programming languages and comments 2448written in a syntax for comments that may be based on the programminglanguage in which the executable instructions 2447 are written. Itshould be noted that, for the sake of understandability in presentation,what is depicted is a deliberately simplified example of a task routine2440 in which there is a single block of comments 2448 that precedes asingle block of executable instructions 2447. As also depicted, and inkeeping with the earlier discussed approaches to enabling the automatedselection of task routines 2440 to perform specific tasks, the depictedexample task routine 2440 may include the flow task identifier 2241 thatidentifies the particular task that is performed by the task routine2440.

As also depicted, and in keeping with the earlier discussed approachesto organizing task routines 2440 for later retrieval and use, thedepicted example task routine 2440 may be stored within a federated area2566 in which a task routine database 2564 may also be stored that mayemploy an indexing scheme by which the task routine 2440 is able to beretrieved by the task routine identifier 2441 assigned to it. As has wasalso previously discussed, the task routine database 2564 may correlateflow task identifiers 2241 of tasks to be performed with task routineidentifiers 2441 of the task routine(s) 2440 that perform each of thosetasks. However, as previously noted, other mechanisms than a databasemay be employed to enable the retrieval of task routines 2440 for use inthe performances of their respective tasks during the performance of ajob flow. As has also been discussed, the federated area 2566 in whichthe depicted example task routine 2440 is stored may be one of a set ofmultiple related federated areas 2566, such as a linear hierarchy or ahierarchical tree. Thus, as depicted, the portal data 2539 (or otherdata structure) may store various parameters associated with each of themultiple federated areas 2566 within such a set of federated areas 2566,including aspects of relationships thereamong, and separate federatedarea identifiers 2568 and/or 2569 for each.

In executing the interpretation component 2547, the processor(s) 2550 ofthe one or more federated devices 2500 may be caused to parse thecomments 2448 (whether divided into multiple blocks throughout the taskroutine 2440, or not) to identify, retrieve and interpret at leastportions of the comments 2448 that specify aspects of inputs and/oroutputs of the task routine 2440. Such aspects that may be so specifiedmay include, and are not limited to, data types of data objects receivedas inputs and/or generated as outputs, and/or indexing schemes that maybe employed in accessing data within data objects. Some of such comments2448 may identify particular data objects used as inputs and/orgenerated as outputs, and this may be done to provide default selectionsof data objects. Alternatively, others of such comments 2448 may avoiddoing so as part of an approach to allowing particular data object(s) tobe specified by a job flow definition, or in any of a variety of otherways, during the performance of a job flow in which the task routine maybe executed. In parsing the comments 2448, the processor(s) 2550 may becaused to retrieve various rules for interpreting the contents of thetask routine 2440 from a stored set of parameter rules 2537, includinglanguage interpretation rules for at least the particular programminglanguage in which the task routine 2440 was written. The processor(s)2550 may be caused to use such rules to distinguish the comments 2448from at least the executable instructions 2447, and may use such rulesto interpret them.

In further executing the interpretation component 2547, the processor(s)2550 of the one or more federated devices 2500 may be caused to generatea macro 2470 corresponding to the task routine 2440 that includes one ormore input/output (I/O) parameters 2478 that indicate the detailsconcerning inputs and/or outputs that are retrieved from the executableinstructions 2447 and/or the comments 2448 of the task routine 2440.Additionally, other pieces of information may also be included in themacro 2470, such as the flow task identifier 2241 indicating the taskperformed when the task routine 2440 is executed, and/or the federatedarea identifiers 2568 and/or 2569 of the federated area 2566 in whichthe depicted example task routine 2440 is stored.

In some embodiments, the processor(s) 2550 of the one or more federateddevices 2500 may additionally compare aspects of inputs and/or outputsindicated in the comments 2448 to how those aspects are actuallyimplemented in the executable instructions 2447 to determine whetherthey match. Where discrepancies are detected, side by side sets of I/Oparameters 2478 may be stored within the depicted example macro 2470,with one based on the comments 2448 and the other based on theexecutable instructions 2447, as a way of indicating a discrepancytherebetween. This may be deemed desirable to allow the details of sucha discrepancy to be displayed as part of the DAG 2270 that is latergenerated from the macro 2470.

Turning to FIG. 19B, as depicted, an example DAG 2270 may be generatedand then visually presented in an example visualization 2980 in whichthe example task routine 2440 of FIG. 19A is represented with acombination of graph objects, including a task graph object 2984accompanied by an input data graph object 2983 and an output data graphobject 2987. It should be noted that, for the sake of understandabilityin presentation, what is depicted is a deliberately simplified exampleof a DAG 2270 in which there is a single task routine 2440 depicted thathas a single input and a single output. However, it is envisioned thatother embodiments of the DAG 2270 may be generated that may includerepresentations of a great many task routines 2440 of which many wouldmay include multiple inputs and/or multiple outputs.

As depicted in the example visualization 2980, the graph objects 2983,2984 and 2987 that form such a representation of the task routine 2440of FIG. 19A may each be selected to visually conform, to at least somedegree, to version 2.0 of the BPMN specification for visualrepresentations of objects. More specifically, a rounded rectangle maybe selected to be the task graph object 2984, and circles connected tothe task graph object 2984 by arrows may be selected to be the datagraph objects 2983 and 2987. In generating the task graph object 2984,some form of identifier of the task routine 2440 may be placed withinthe rounded rectangle shape thereof. In some embodiments, such anidentifier may be the task routine identifier 2441 assigned to the taskroutine 2440 and/or the flow task identifier 2241 that identifies thetask performed by the task routine 2440, each of which may be includedwithin and retrieved from the macro 2470. However, as previouslydiscussed, at least the task routine identifier 2441 may be a hash valueof numerous bytes in size generated by taking a hash of at least aportion of the task routine 2440 such that the task routine identifier2441 may be cumbersome for personnel to read, recognize and use as amechanism to uniquely identify the task routine 2440. Therefore, thetask routine 2440 may be assigned a less cumbersome textual name thatmay be placed within the rounded rectangle shape of the task graphobject 2984. It may be that such an assigned textual name may be basedon a name given to the file in which the task routine 2440 is stored inembodiments in which objects are stored within the federated area(s)2566 as files with textual file names. Alternatively or additionally, itmay be that such an assigned textual name may be specified in thecomments 2448 of the task routine 2440.

Additionally, in embodiments in which the task routine 2440 is storedwithin a federated area 2566 that belongs to a set of related federatedareas 2566, some form of identifier of the specific federated area 2566in which the task routine 2440 is stored may be placed within therounded rectangle shape of the task graph object 2984. In someembodiments, such an identifier may be the human-readable federated areaidentifier 2568. As previously discussed, it may be that thehuman-readable federated area identifier 2568 is a URL that may includea textual name given to the federated area 2566, and may additionallyindicate a path among multiple federated areas 2566 by which thefederated area 2566 that stores the task routine 2440 is connected to abase federated area 2566 (unless the federated area 2566 in which thetask routine 2440 is stored is the base federated area). Further, inembodiments in which the human-readable federated area identifier 2568is a URL and in which the task routine 2440 is assigned a textual namebased on a file name, the human-readable federated area identifier 2568may be combined with such a name into a single string of text within therounded rectangle that both identifies the task routine 2440 andspecifies its location among the set of related federated areas 2566 inrelation to the base federated area thereof.

In generating the input data graph object 2983, some form of identifierof the input data object represented thereby may be placed within oradjacent to the input data graph object 2983. Similarly, in generatingthe output data graph object 2987, some form of identifier of the outputdata object represented thereby may be placed within or adjacent to theoutput data graph object 2987. As previously discussed, the comments2448 within a task routine 2440 may provide a more or less specificindication of a data object serving as an input or an output, and thismay depend on whether it is intended that a data object is to bespecified when the task routine 2440 is executed as part of aperformance of a job flow, or the identity of the data object is alreadyknown such that it is able to be specifically identified in the comments2448.

Focusing, for sake of ease of discussion, on the input data graph object2983, if the identity of the specific data object for this input (e.g.,the depicted example data set 2330) is already known at the time thetask routine 2440 is written, then some form of identifier of thatspecific data object may be specified in the comments 2448 and/or in theexecutable instructions 2447. In some embodiments, such an identifiermay be the data object identifier 2331 assigned to the depicted exampledata set 2330. However, as previously discussed, as with the taskroutine identifier 2441 of the task routine 2440, the data objectidentifier 2331 may also be a hash value of numerous bytes in size suchthat the data object identifier 2331 may also be cumbersome forpersonnel to read, recognize and use. Therefore, as with the taskroutine 2440, the depicted data set 2330 may be assigned a lesscumbersome textual name that may be incorporated into its data setmetadata 2338, and this textual name may be placed within or adjacent tothe circular input data graph object 2983. As with such a textual namethat may be assigned to the task routine 2440, such a textual nameassigned to the data set 2330 may be based on a name given to the filein which the data set 2330 is stored in embodiments in which objects arestored within the federated area(s) 2566 as files with textual filenames.

However, and still focusing on the input data graph object 2983, if theidentity of the specific data object for this input is not already knownat the time the task routine 2440 is written, then the name of avariable or some other form of placeholder may be specified in thecomments 2448 and/or in the executable instructions 2447. In suchembodiments, it may be the name or other identifier of that variable orother type of placeholder that may be placed within or adjacent to thecircular input data graph object 2983. It should be noted that suchapproaches to providing a visual indication of the identity of the inputdata object associated with the depicted input data graph object 2983may also be applied to providing a visual indication of the identity ofthe output data object (not shown) associated with the depicted outputdata graph object 2987.

FIGS. 19C and 19D, taken together, depict an embodiment of an approachto conveying either the presence of a dependency or the lack of adependency between two task routines in visualizations 2980 ofcontrasting examples of DAGs 2270. Each of the example visualizations2980 of FIGS. 19C and 19D includes representations of two task routines2440 a and 2440 b, where the task routine 2440 a is represented by acombination of a task graph object 2984 a and corresponding data graphobjects 2983 and 2987, and where the task routine 2440 b is representedby a combination of a task graph object 2984 b and other correspondingdata graph objects 2983 and 2987. However, in the visualization 2980 ofFIG. 19C, a vertical arrangement of the representations of the taskroutines 2440 a and 2440 b is used to provide a visual indication of nodependency therebetween, such that there is no data object output by oneof the task routines 2440 a and 2440 b that is needed as an input to theother. In contrast, in the visualization 2980 of FIG. 19D, a horizontalarrangement of the representations of the task routines 2440 a and 2440b provides the suggestion of a left-to-right path of dependency from thetask routine 2440 a to the task routine 2440 b. Reinforcing thisindication of such a dependency is an additional arrow pointing from therepresentation of the task routine 2440 a to the representation of thetask routine 2440 b. It should be noted that, although such a use of anarrow is depicted as providing an indication of such a dependency(regardless of whether horizontal arrangement is also used), any of avariety of other forms of indication of such a dependency may be used inother embodiments. By way of example, color coding, graphical symbolsand/or other form of visual connector indicative of the dependency maybe used to.

In situations, in which a visualization 2980 is to be generated of a DAG2270 that includes multiple task routines 2440, the details of theinputs and outputs of each of the task routines may be analyzed toidentify any instances that may be present of a particular data objecthaving been specified as both an output of one task routine 2440 and aninput of another task routine 2440. Such a situation, if found, may bedeemed to indicate a dependency in which the one task routine 2440provides the particular data object that is needed as an input to theother 2440, such as what is depicted in FIG. 19D between the output oftask routine 2440 a and the input of task routine 2440 b. Again, as aresult of such a dependency, execution of the task routine 2440 a may berequired to occur ahead of the execution of the task routine 2440 b soas to ensure that the output of the task routine 2440 a is able to beprovided to the task routine 2440 b for use during its execution.

FIG. 19E depicts aspects of the generation and storage, within afederated area 2566, of a new DAG 2270 from a visualization 2980 of anearlier DAG 2270 that may have been edited. More specifically, in someembodiments a UI may be provided to allow editing of aspects of one ormore task routines 2440 of an existing DAG 2270 by graphically editingcorresponding aspects of graph objects 2983, 2984 and/or 2987 of one ormore corresponding representations of task routines 2440. Thus, where avisualization 2980 is initially generated of a DAG 2270, provision maybe made for such editing to allow details of a new DAG 2270 to bedeveloped. Further, upon completion of such editing, the new DAG 2270thusly developed may then be stored within a federated area 2566, andmay subsequently be used as at least a basis for a new job flowdefinition 2220 that defines a new job flow.

Such editing may entail changing the visual indication(s) of one or moreI/O parameters 2478 that may be visually indicated within or adjacent toan input data graph object 2983 or an output data graph object 2987 tothereby change the one or more I/O parameters 2478 that correspond tothose visual indication(s). More specifically, where a name or otheridentifier of a data object 2330 or 2370 that is generated as an outputof a task routine 2440 is visually presented adjacent to thecorresponding output data graph object 2987, an edit made in which thatname or other identifier is changed in the visualization 2980 maytrigger a corresponding change in what data object 2330 or 2370 isgenerated as an output. Correspondingly, where a name or otheridentifier of a data object 2330 or 2370 that is used as an input to atask routine 2440 is visually presented adjacent to the correspondinginput data graph object 2983, an edit made in which that name or otheridentifier is changed in the visualization 2980 may trigger acorresponding change in what data object 2330 or 2370 is used as aninput. As a result of such editing capabilities being provided,dependencies between task routines may be created, changed and/orentirely removed. In at least this way, the order of performance oftasks, and/or which tasks are able to be performed in parallel, may bechanged as part of creating a new DAG 2270 that may be employed as atleast part of a new job flow definition 2220.

As previously discussed, a DAG 2270 may be stored in a federated area asa script generated in a process description language such as BPMN. Insome embodiments, at least a subset of the job flow definitions 2220maintained within one or more federated areas 2566 by the one or morefederated devices 2500 may also be stored, at least partially, asscripts in such a process description language as BPMN. Thus, there maybe few, if any, differences in the contents of DAGs 2270 vs. job flowdefinitions 2220 such that a DAG 2270 may be usable as a job flowdefinition 2220 with little or no modification. It is for this reasonthat DAGs 2270 may be stored alongside job flow definitions 2220 in theearlier described job flow database 2562.

FIG. 20 illustrate aspects of an example embodiment of the distributedprocessing system 2000 that supports a collaborative effort to developan analysis routine that is implemented as a job flow, where thecollaboration is between developers who have direct access to and usethe one or more federated areas 2566 maintained by the one or morefederated devices 2500, and other developers who may not have access tothe one or more federated areas 2566 and/or are not familiar with how touse the one or more federated areas 2566. It may also be that thedevelopers having access to the one or more federated areas 2566 arealso familiar with a primary programming language that is utilized bythe processor(s) 2550 of the one or more federated devices 2500 inperforming job flows, while the other developers are more familiar withone or more secondary programming languages that are not normally soutilized by the processor(s) 2550.

The other developers may be more familiar with the use of a source codemanagement routine implemented by the depicted control routine 2140 or2840 by which a source device 2100 or a reviewing device 2800,respectively, may be operated as a source code repository that enforcesa set of procedures for managing collaborative development amongmultiple developers as will be familiar to those skilled in the art. Itmay further be that the other developers are not familiar withimplementing an analysis routine as a job flow defined by a job flowdefinition 2220 that defines the analysis as a set of tasks to beperformed in a particular order by a set of task routines 2440. As isabout to be explained in greater detail, the one or more federateddevices 2500 may be caused to repeatedly communicate with the otherdevice 2100 or 2800 in which such a repository of executableinstructions is maintained to effect exchanges of objects therebetweenas part of enabling the collaboration between the developers who use thefederated areas 2566 and the developers who use the repositorymaintained within the other device 2100 or 2800.

This collaborative development of the analysis routine as a job flow maybe based on a presumption that this job flow is to be performed usingthe distributed processing and storage resources of the one or morefederated devices 2500. As a result, many of the objects developed bythe developers who employ the other device 2100 or 2800 as a source coderepository and who write executable instructions in one or moresecondary programming languages may be transferred in a unidirectionalmanner from the other device 2100 or 2800 to the one or more federateddevices 2500. Such objects may include task routines includingexecutable instructions written in a secondary language, which aredesignated as task routines 2440 s to aid in distinguishing those taskroutines from others that include executable instructions written in theprimary language, which are designated as task routines 2440 p. However,there may be some objects that may be transferred in a bidirectionalmanner between the other device 2100 or 2800 and the one or morefederated devices 2500. Such objects may include job flow definitionsthat include portions written in a secondary language, which aredesignated as job flow definitions 2220 s to distinguish them from otherjob flow definitions that include portions written in the primaryprogramming language, which are designated as job flow definitions 2220p.

Although data objects such as data sets 2330 or 2370 may include noexecutable instructions, as those skilled in the art will readilyrecognize, differences in programming languages may include differencesin data types that are supported and/or differences in theorganizational aspects of the formatting and/or indexing of data itemswithin such large and/or complex data structures as arrays. Thus, and aswill be explained in greater detail, there may be different forms of adata set 2330 or 2370 that are meant to accommodate such differences inprogramming languages. Data objects that are of a form meant toaccommodate at least task routines 2440 s that include executableinstructions written in a secondary language are designated as data sets2330 s or 2370 s to distinguish them from data objects that are of aform meant to accommodate at least task routines 2440 p that includeexecutable instructions written in the primary language, which aredesignated as data sets 2330 p or 2370 p.

As depicted in FIG. 20, the storage 2160 or 2860 of the other device2100 or 2800 may store the control routine 2140 or 2840, respectively,that may implement the logic of the source code management system bywhich portions of executable instructions (e.g., text files that havebeen generated to include executable instructions) may be stored withinthe storage 2160 or 2860 as a repository of portions of executableinstructions that is managed according to a set of rules that at leastaid in preventing the generation and/or editing of portions ofexecutable instructions in a manner that creates conflicting portions ofexecutable instructions. As will be familiar to those skilled in theart, some of such source code management systems enforce a requirementthat a portion of executable instructions that is to be edited must be“checked out” from the repository, which has the effect of “locking” itsuch that no other developer can also check it out until it has been“checked in” again. Alternatively or additionally, some of such sourcecode management systems may allow the “checking out” of a portion ofexecutable instructions to multiple developers, and may then employ anyof a variety of techniques to resolve differences in multiple editedversions of that portion of executable instructions that aresubsequently “checked in” again. Also alternatively or additionally,some of such source code management systems are meant to operatecooperatively with a compiler to enable the identification of recently“checked in” portions of executable instructions that prevent asuccessful compiling of the portions of executable instructions withinthe repository to enable selected ones of such recently “checked in”portions of executable instructions to be “backed out” of therepository, thereby restoring an earlier version of those selectedportions of executable instructions that may enable a successfulcompiling.

As part of implementing such source code management functionality,messages may be transmitted to developers (e.g., emails, text messaging,etc.) that inform them of when particular portions of executableinstructions of interest to them have been “checked out” or “checked in”by another developer and/or when a portion of executable instructionsthat they had “checked in” was subsequently “backed out” to enable asuccessful compilation. Regardless of the exact manner in which a sourcecontrol management system may be implemented within the other device2100 or 2800, information concerning the status of each portion ofexecutable instructions (e.g., whether a portion is currently “checkedout” and/or whether a portion needed to be “backed out”) may bemaintained as part of a transfer metadata 2163 or 2863. Thus, in thisexample collaboration among developers to implement an analysis routineas a job flow implemented as a combination of a job flow definition andtask routines, the portions of executable instructions authored by thedevelopers who make use of the repository provided by the other device2100 or 2800 may include the depicted job flow definition 2220 s and/orone or more task routines 2440 s, wherein the executable instructionswithin each may be written by those developers in a secondaryprogramming language.

As also depicted in FIG. 20, a portion of a federated area 2566 may bedesignated as the transfer area 2666 within which objects that areexchanged with the other device 2100 or 2800 may be held. As previouslydiscussed, the processor(s) 2550 of the one or more federated devices2500 may be caused by execution of the portal component 2549 to maintaina synchronization relationship in which the contents of the transferarea 2666 are to be kept synchronized with the contents of a portion ofthe storage 2160 or 2860 of the other device 2100 or 2800 that has beendesignated as the transfer area 2166 or 2866, respectively.

In some embodiments, the one or more federated devices 2500 and theother device 2100 or 2800 may both be caused to actively cooperate witheach other to maintain synchronization of the contents between thetransfer area 2666 and the other transfer area 2166 or 2866. By way ofexample, in such embodiments, the transfer area 2666 within thefederated area 2566 maintained by the one or more federated devices 2500may be designated as a secondary repository location as part of creatinga geographically distributed repository in which the other device 2100or 2800 interacts with the one or more federated devices 2500 as a peerrepository device. It may be that a link or pointer (e.g., a networkaddress, a URL or other identifier of the one or more federated devices2500 and/or of the transfer area 2666 is provided to the other device2100 or 2800 and/or is stored within the transfer metadata 2163 or 2863for use by the other device 2100 or 2800, respectively, in contactingthe one or more federated devices 2500 via the network 2999 andaccessing the transfer area 2666 to maintain its contents insynchronization with the contents of the other transfer area 2166 or2866. In this way, the other device 2100 or 2800 may actively providecopies of new objects and/or updated copies of existing altered objectswithin the transfer area 2166 or 2866 to the one or more federateddevices 2500 for storage within the transfer area 2666, and/or mayactively retrieve copies of new objects and/or updated copies existingaltered objects from the transfer area 2566 and store those copieswithin the other transfer area 2166 or 2866. It may be that, as part ofsuch cooperation, the one or more federated devices 2500 exchangeinformation with the other device 2100 or 2800 concerning the currentstate of objects stored within each of the transfer area 2566 and theother transfer area 2166 or 2866.

Alternatively or additionally, in other embodiments, the other device2100 or 2800 may be caused to interact with the one or more federateddevices 2500 as a user that has been granted access to the federatedarea 2566 in which the transfer area 2666 is maintained. The otherdevice 2100 or 2800 may be provided with log in credentials (which maybe stored within the transfer metadata 2163 or 2863) that enable theother device 2100 or 2800 to be authorized to log into that federatedarea and to store and/or remove objects within the transfer area 2666.In such other embodiments, the other device 2100 or 2800 may be providedwith a link or pointer to the transfer area 2666, and may be configuredto use the transfer area 2666 as a remotely located network storagedevice that is to be used as the storage location within which therepository is to be maintained. Thus, in such other embodiments, it maybe that transfer area 2166 or 2866 is employed by the other device 2100or 2800, respectively, as a buffer storage location in which thecontents of the transfer area 2666 are buffered, at least duringtransfers to and/or from the transfer area 2666.

As still another alternative, in still other embodiments, the one ormore federated devices 2500 may be caused to interact with the otherdevice 2100 or 2800 as a user that has been granted access to therepository maintained within the transfer area 2166 or 2866,respectively. The one or more federated devices 2500 may be providedwith log in credentials (which may be stored within the transfermetadata 2563) that enable the one or more federated devices 2500 to beauthorized to log into the other device 2100 or 2800, and to retrievecopies of the entirety of contents of the repository, and/or to “checkin” and/or “check out” individual objects just as any of the developerswho use the other device 2100 or 2800 would. In such other embodiments,the other device 2100 or 2800 may be provided with communicationsinformation required to transmit messages (e.g., emails and/or textmessages) to the one or more federated devices 2500 that provideindications of occasions when objects within the repository (e.g.,within the transfer area 2166 or 2866) have been added, changed and/orremoved, and/or indications of occasions when objects have been “checkedin”, “checked out” and/or “backed out” to the one or more federateddevices 2500 as a developer.

Regardless of the exact manner in which exchanges of objects are causedto occur between the transfer areas 2666, and 2166 or 2866, upon thereceipt of job flow definitions 2220 s and/or task routines 2440 s thatinclude portions written in a secondary programming language that eitherdefine or implement input and/or output interfaces, such portions may betranslated into an intermediate programming language (or otherintermediate representation) to enable comparisons to correspondingportions of task routines 2440 p that have been translated from theprimary programming language into the same intermediate programminglanguage (or other intermediate representation). As has been discussed,the results of such comparisons may determine whether each of suchreceived job flow definitions 2220 s and/or each of such task routines2440 s will be stored within a federated area 2566. Further, and as alsopreviously discussed, a job flow definition 2220 s that is determined tobe permitted to be stored within a federated area 2566 may actually beso stored in a translated form (namely, as a job flow definition 2220 p)in which the portions written in the secondary programming language aretranslated into the primary programming language.

FIGS. 21A, 21B, 21C, 21D and 21E, together, illustrate the manner inwhich a task routine 2440 s that includes executable instructionswritten in a secondary programming language may be selectively storedwithin a federated area 2566 maintained by the one or more federateddevices 2500. FIG. 21A illustrates aspects of the receipt of the taskroutine 2440 s. FIGS. 21B-C, together, illustrate aspects of identifyingother task routines 2440 s or 2440 p that may already be stored and thatperform the same task as the received task routine, and comparing inputand/or output interfaces therewith. FIGS. 21D-E, together, illustrateaspects of the storage of the task routine 2440 s and/or the generationand transmission of a DAG 2270 based on the comparison.

Turning to FIG. 21A, as previously discussed, the one or more federateddevices 2500 may receive the task routine 2440 s from another device2100 or 2800 as part of an exchange of objects in response to a requestto perform any of a variety of operations, or as part of an exchange ofobjects associated with synchronizing transfer areas. Where the taskroutine 2440 s is received in an exchange associated with a request fromthe other device 2100 or 2800, the processor(s) 2550 of the one or morefederated devices 2500 may temporarily store the task routine 2440 s aspart of the request data 2535 maintained by at least one of the one ormore federated devices 2500 as a buffer for received requests. Where thetask routine 2440 s is received in an exchange as part of asynchronization of the transfer area 2666 with the other transfer area2166 or 2866, the processor(s) 2550 may at least temporarily store thetask routine 2440 s within the transfer area 2666.

Turning to FIG. 21B, regardless of where exactly the now received taskroutine 2440 s is stored within the one or more federated devices 2500,the processor(s) 2550 thereof may be caused by the admission component2542 to retrieve the flow task identifier 2241 from the task routine2440 s that identifies the task that it performs. The processor(s) 2550may then be caused by the admission component 2542, in conjunction withthe database component 2545, to use the flow task identifier 2241 tosearch for, identify and retrieve any task routines 2440 s and/or 2440 pwithin the one or more federated areas 2566 that also perform the sametask.

Turning to FIG. 21C, presuming that one or more of such task routines2440 s and/or 2440 p were identified in the one or more federated areas2566, the processor(s) 2550 of the one or more federated devices 2500may be caused by the admission component 2547 to retrieve, from thereceived task routine 2440 s, portion(s) of the comments 2448 s that mayset forth details of the input and/or output interface(s) 2443 and/or2444 of the received task routine 2440 s (if there is any portion of thecomments 2448 s that does so), and/or may be caused to retrieveportion(s) of the executable instructions 2447 s that implement theinput and/or output interfaces 2443 and/or 2444. The processor(s) 2550may be further caused by the admission component 2542 to translate suchportion(s) of the comments 2448 s and/or of the executable instructions2447 s from the secondary programming language into an intermediaterepresentation 2532 of the manner in which input and/or outputinterfaces are implemented in the received task routine 2440 s.Similarly, the processor(s) 2550 of the one or more federated devices2500 may be caused by the admission component 2542 to similarly retrieveand translate such portion(s) of the comments 2448 p and/or 2448 s,and/or such portion(s) of the executable instructions 244′7 p and/or2447 s within each of the identified task routines 2440 p and/or 2440 s,respectively, from the primary programming language or a secondaryprogramming language into a corresponding intermediate representation2532 of the manner in which input and/or output interfaces areimplemented therein. With such intermediate representations 2532 havingbeen so generated, the processor(s) 2550 may be caused by the admissioncomponent 2542 to compare each of these implementations of input and/oroutput interfaces, as described in the intermediate representations2532, to determine if there is a sufficient match.

In so doing, the processor(s) 2550 may be caused by the admissioncomponent 2542 to retrieve various rules for the performance of thecomparison of input interfaces and/or various rules for the performanceof the comparison of output interfaces from admission rules 2532. As hasbeen previously discussed, it may be deemed permissible for inputinterfaces 2443 and/or 2444 of a newly received task routine 2440 s or2440 p to either be identical to the input interfaces 2443 and/or 2444of task routine(s) already stored within the one or more federated areas2566, or to be supersets thereof if the newly added portions of thoseinput interfaces 2443 and/or 2444 do not require input. As has also beenpreviously discussed, it may be deemed permissible for output interfaces2443 and/or 2444 of a newly received task routine 2440 s or 2440 p toeither be identical to the output interfaces 2443 and/or 2444 of taskroutine(s) already stored within the one or more federated areas 2566,or to be supersets thereof, since the newly added portions of thoseoutput interfaces 2443 and/or 2444 could simply be ignored by anothertask routine 2440 s or 2440 p that does not use them.

Turning to FIG. 21D, if no other task routines 2440 s and/or 2440 p thatperform the same task were identified in the search performed in FIG.21B, or if there was a sufficient match among input and/or outputinterfaces 2443 and/or 2444 found in the comparison performed in FIG.21C, then as depicted in FIG. 21D, the processor(s) 2550 of the one ormore federated devices 2500 may be caused by the admission component2542, in conjunction with the database component 2545, to store thenewly received task routine 2440 s in a federated area 2566, or to allowthe newly received task routine 2440 s to remain stored therein inembodiments in which it may already be stored therein as a result ofbeing stored within the transfer area 2666 therein. In so doing, theprocessor(s) 2550 may be caused by the identifier component 2541 toassign a task routine identifier 2441 s to the newly received and nowstored task routine 2440 s.

Turning to FIG. 21E, if one or more other task routines 2440 s and/or2440 p that perform the same task were identified in the searchperformed in FIG. 21B, and if there was found to be an insufficientmatch between the implementation of the input and/or output interfaces2443 and/or 2444 of the received task routine 2440 s and theimplementation of those same interfaces of any of the identified taskroutines 2440 p and/or 2440 s in the comparison performed in FIG. 21C,then as depicted in FIG. 21E, the processor(s) 2550 of the one or morefederated devices 2500 may be caused by the interpretation component2547 to generate a DAG 2270 that provides a visual indication of thenature of the mismatch in interfaces. The processor(s) 2550 may then becaused by the portal component 2549 to transmit the DAG 2270 via thenetwork 2999 to the other device 2100 or 2800 from which the taskroutine 2440 s was received to enable a visual indication of themismatch to be visually presented on a display 2180 or 2880,respectively, thereof. In some embodiments, the received task routine2440 s would not then be stored within a federated area 2566, or may beremoved therefrom if it had already been stored therein on a temporarybasis.

However, in other embodiments where the task routine 2440 s was receivedas part of a synchronization relationship among transfer areas, it may,instead, be deemed more desirable to proceed with storing the taskroutine 2440 s within a federated area 2566, or allowing it to remain sostored in the federated area 2566 in which the transfer area 2666 hasbeen instantiated. In such embodiments, the generation of the DAG 2270may be deemed a sufficient action to take in response to such a mismatchas it provides a warning concerning the mismatch.

FIGS. 22A, 22B, 22C, 22D and 22E, together, illustrate the manner inwhich a job flow definition 2220 s that includes executable instructionswritten in a secondary programming language may be selectively storedwithin a federated area 2566 maintained by the one or more federateddevices 2500. FIG. 22A illustrates aspects of the receipt of the jobflow definition 2220 s. FIGS. 22B-C, together, illustrate aspects ofidentifying task routines 2440 s or 2440 p that may already be storedand that each perform one of the tasks of the job flow defined by thereceived job flow definition 2220 s, and comparing input and/or outputinterfaces therewith. FIGS. 22D-E, together, illustrate aspects of thestorage of the job flow definition 2220 s and/or the generation andtransmission of a DAG 2270 based on the comparison.

Turning to FIG. 22A, as previously discussed, the one or more federateddevices 2500 may receive the job flow definition 2220 s from anotherdevice 2100 or 2800 as part of an exchange of objects in response to arequest to perform any of a variety of operations, or as part of anexchange of objects associated with synchronizing transfer areas. Wherethe job flow definition 2220 s is received in an exchange associatedwith a request from the other device 2100 or 2800, the processor(s) 2550of the one or more federated devices 2500 may temporarily store the jobflow definition 2220 s as part of the request data 2535 maintained by atleast one of the one or more federated devices 2500 as a buffer forreceived requests. Where the job flow definition 2220 s is received inan exchange as part of a synchronization of the transfer area 2666 withthe other transfer area 2166 or 2866, the processor(s) 2550 may at leasttemporarily store the job flow definition 2220 s within the transferarea 2666.

Turning to FIG. 22B, regardless of where exactly the now received jobflow definition 2220 s is stored within the one or more federateddevices 2500, the processor(s) 2550 thereof may be caused by theadmission component 2542 to retrieve, from the flow definition 2222 ofthe job flow definition 2220 s, the flow task identifiers 2241 thatidentify each of the tasks that are specified as part of the job flow bythe job flow definition 2220 s. The processor(s) 2550 may then be causedby the admission component 2542, in conjunction with the databasecomponent 2545, to use each of those flow task identifiers 2241 tosearch for, identify and retrieve task routines 2440 s and/or 2440 pwithin the one or more federated areas 2566 that perform each of thosetasks.

Turning to FIG. 22C, presuming that one or more of such task routines2440 s and/or 2440 p were identified in the one or more federated areas2566, the processor(s) 2550 of the one or more federated devices 2500may be caused by the admission component 2542 to retrieve, from thereceived job flow definition 2220 s, portion(s) of the comments 2228 sthat may set forth details of the input and/or output interface(s) 2443and/or 2444 of each of the tasks specified in the received job flowdefinition 2220 s (if there is any portion of the comments 2228 s thatdoes so), and/or may be caused to retrieve portion(s) of the executableinstructions 2227 s that may also set forth details of those inputand/or output interfaces 2443 and/or 2444. The processor(s) 2550 may befurther caused by the admission component 2542 to translate suchportion(s) of the comments 2228 s and/or of the executable instructions2227 s from the secondary programming language into a separateintermediate representation 2532 of the manner in which the input and/oroutput interfaces associated with each task are specified in thereceived job flow definition 2220 s. Similarly, the processor(s) 2550 ofthe one or more federated devices 2500 may be caused by the admissioncomponent 2542 to similarly retrieve and translate such portion(s) ofthe comments 2448 p and/or 2448 s, and/or such portion(s) of theexecutable instructions 2447 p and/or 2447 s within each of theidentified task routines 2440 p and/or 2440 s, respectively, from theprimary programming language or a secondary programming language into acorresponding intermediate representation 2532 of the manner in whichinput and/or output interfaces are implemented therein. With suchintermediate representations 2532 having been so generated, theprocessor(s) 2550 may be caused by the admission component 2542 tocompare the specifications of the input and/or output interfaces foreach task specified in the received job flow definition 2220 s to theimplementations of input and/or output interfaces of corresponding onesof the identified task routines 2440 p and/or 2440 s, as described inthe intermediate representations 2532, to determine if there is asufficient match.

In so doing, the processor(s) 2550 may be caused by the admissioncomponent 2542 to retrieve various rules for the performance of thecomparison of input interfaces and/or various rules for the performanceof the comparison of output interfaces from admission rules 2532. As hasbeen previously discussed, it may be deemed permissible for inputinterfaces 2443 and/or 2444 actually implemented by task routines 2440 sand/or 2440 p to either be identical to the input interfaces 2443 and/or2444 specified in a job flow definition 2220 s or 2220 p, or to besupersets thereof if the portions of those input interfaces 2443 and/or2444 that go beyond what is specified by the job flow definition 2220 sor 2220 p do not require input. As has also been previously discussed,it may be deemed permissible for output interfaces 2443 and/or 2444actually implemented by task routines 2440 s and/or 2440 p to either beidentical to the output interfaces 2443 and/or 2444 specified in a jobflow definition 2220 s or 2220 p, or to be supersets thereof, since theportions of those output interfaces 2443 and/or 2444 that go beyond whatis specified by the job flow definition 2220 s or 2220 p could simply beignored by another task routine 2440 s or 2440 p that does not use them.

Turning to FIG. 22D, if there was a sufficient match between inputand/or output interface definitions provided in the received job flowdefinition 2220 s and the implementations of the corresponding inputand/or output interfaces 2443 and/or 2444 of corresponding ones of theidentified task routines found in the comparison performed in FIG. 22C,then as depicted in FIG. 22D, the processor(s) 2550 of the one or morefederated devices 2500 may be caused by the interpretation component2547 to generate a translated form of the received job flow definition2220 s for storage within a federated area, namely the depicted job flowdefinition 2220 p. In so doing, the processor(s) 2550 may be caused bythe admission component 2542 to generate at least a portion of thecontents of the job flow definition 2220 p (e.g., the flow definition2222 and/or the interface definitions 2224) from the intermediaterepresentations 2532 of the input and/or output interfaces that wereearlier generated from the specifications of input and/or outputinterfaces of the received job flow definition 2220 s for use in thecomparison performed in FIG. 22C.

Alternatively or additionally, the processor(s) 2550 may be caused bythe interpretation component 2547 to perform a fuller translation of thecontents of the received job flow definition 2220 s from a secondaryprogramming language to the primary programming language. As has beendiscussed, this may be deemed desirable to enable the translation of anyportion of the executable instructions 2227 s that implement a GUI intothe GUI instructions 2229 within the job flow definition 2220 p. In sodoing, the processor(s) 2550 may be caused to retrieve indications ofvarious rules and/or parameters that control the translations performedbetween programming languages from the interpretation rules 2537. Amongthose parameters and/or rules may be various syntax rules for thecomments 2448 in the primary and/or secondary programming languages(e.g., punctuation marks that separate human-readable comments fromexecutable instructions, etc.), syntax rules for executable instructionsin the primary and/or secondary programming languages, and/or items ofvocabulary for each programming language correlated to the other. Alsoamong those parameters and/or rules may also be rules for interpretingthe specifications and/or implementations of input and/or outputinterfaces in comments and/or in executable instructions. Further amongthose parameters and/or rules may be indications of supported data typesof the primary and secondary languages, as well as correlationstherebetween and rules for conversions of data types therebetween (e.g.,rules for performing serialization and/or de-serialization).Additionally among those parameters and/or rules may be rules foridentifying executable instructions in the secondary language thatimplement a GUI that is to be translated to generate the GUIinstructions 2229.

In conjunction with the database component 2545, the processor(s) 2550may be caused by the admission component 2542 to store the newlygenerated job flow definition 2220 p in a federated area 2566. In sodoing, the processor(s) 2550 may be caused by the identifier component2541 to assign a task routine identifier 2221 p to the newly generatedand stored job flow definition 2220 p. Further, in some embodiments andas previously discussed, the originally received job flow definition2220 s may also be stored in a federated area 2566. In such embodiments,the translated form 2220 p thereof may be generated to additionallyinclude the job flow identifier 2221 s of the originally received jobflow definition 2220 s as a measure to provide accountability for theaccuracy of the translation by identifying the job flow definition 2220s from which the translation was made to enable a subsequent analysis.

Turning to FIG. 22E, if there was found to be an insufficient matchamong the input and/or output interfaces 2443 and/or 2444 in thecomparison performed in FIG. 22C, then as depicted in FIG. 22E, theprocessor(s) 2550 of the one or more federated devices 2500 may becaused by the interaction component to generate a DAG 2270 that providesa visual indication of the nature of the mismatch in interfaces. Theprocessor(s) 2550 may then be caused by the portal component 2549 totransmit the DAG 2270 via the network 2999 to the other device 2100 or2800 from which the job flow definition 2220 s was received to enable avisual indication of the mismatch to be visually presented on a display2180 or 2880, respectively, thereof. In some embodiments, the job flowdefinition 2220 p would not then be generated and stored within afederated area 2566.

However, in other embodiments where the job flow definition 2220 s wasreceived as part of a synchronization relationship among transfer areas,it may, instead, be deemed more desirable to proceed with generating andstoring the job flow definition 2220 p within a federated area 2566. Insuch embodiments, the generation of the DAG 2270 may be deemed asufficient action to take in response to such a mismatch as it providesa warning concerning the mismatch.

FIGS. 23A, 23B, 23C, 23D, 23E, 23F and 23G, together, illustrate anexample embodiment of supporting the use of multiple programminglanguages among a set of task routines 2440 used in performing a jobflow. More specifically, FIGS. 23A-G depict an embodiment of dynamicallyconverting various characteristics of data objects that may be generatedand/or used as inputs by different task routines 2440 that may includeexecutable instructions 2447 that may be written in differingprogramming languages. The term programming language, as used herein, ismeant to refer to a human-readable language in which developer personnelmay write executable instructions (e.g., the executable instructions2447 of a task routine 2440, or the GUI instructions 2229 of job flowdefinition 2220) that may be executable by a processor through use of aruntime interpreter and/or a compiler. Such a programming language mayinclude a high-level language that may employ high-level abstractions ofdata structures, callable routines, executable objects, computing deviceresources, etc., that may enable a developer to write executableinstructions that, when executed, cause the performance of processingoperations, including parallel processing and/or distributed processingoperations. As has been discussed, and as will be familiar to thoseskilled in the art, different programming languages may supportdiffering data types, and/or differing approaches to accessing,organizing and/or indexing data items within arrays and/or other complexdata types.

By way of example, although two programming languages may both supportthe use of a two-dimensional (2D) array, it may be that they supportdifferent varieties of data types for the individual data values withina 2D array, different indexing schemes (e.g., 16-bit indexes vs. 32-bitindexes, or 0-based indexing vs. 1-based indexing), different byteencodings (e.g., little Endian vs. big Endian), different organizationsof elements (e.g., row-column vs. column-row, highest-numbered row firstvs. lowest-numbered row first, or structured vs. unstructured),different separators (e.g., commas vs. empty spaces to separate dataitems or rows of data items), different organizations of row and/orcolumn headings, different text encodings (e.g., ASCII vs. EBCDIC vs.double-byte character set encoding), etc. As a result, relatively minordifferences in the definitions of such structures as 2D arrays betweentwo programming languages may prevent a 2D array generated withexecutable instructions in one programming language from being read byexecutable instructions in another programming language. This may causedata objects 2330, 2370 and/or 2770 that are output by one task routine2440 with executable instructions 2447 written in one programminglanguage to be unusable as input to another task routine 2440 withexecutable instructions 2447 written in another programming languagewithout some degree of conversion being performed to cause such dataobjects to be changed from one form associated with the one programminglanguage to another form associated with the other programming language.

As has also been discussed, it may be that a particular programminglanguage has been selected as the primary language that is, at least bydefault, expected to be used in writing the executable instructions ofthe task routines 2440 that are to be executed by the processor(s) ofthe one or more federated devices 2500 to perform the tasks of a jobflow. Such a designation of a particular programming language as theprimary programming language may necessarily result in the correspondingadoption of various characteristics of the manner in which that primaryprogramming language represents, stores and/or accesses data that may beunique to that primary programming language. As a result, variouscharacteristics of the data objects 2330, 2370 and/or 2770 that may bestored within the one or more federated areas 2566 may be actually bedictated by which programming language is designated to be the primaryprogramming language. This may make the form in which data objects 2330,2370 and/or 2700 may be stored within the one or more federated areas2566 unreadable by executable instructions 2447 of task routines 2440that are not written in the primary programming language without somedegree of conversion being performed to change such data objects fromthe form associated with the primary programming language and used forstorage in federated areas 2566 to another form that is associated withanother programming language and that is not used for storage infederated areas 2566.

Turning to FIG. 23A, as depicted, to accommodate the performances ofsuch conversions of data objects during the performance of a job flow,the processor(s) 2550 of the one or more federated devices 2500 may becaused by the performance component 2544 to instantiate a shared memoryspace 2660. More specifically, the processor(s) 2550 may be caused bythe performance component 2544 to instantiate the shared memory space2660 at the commencement of a performance of a job flow, and toun-instantiate the shared memory space 2660 at the completion of theperformance of that job flow. As depicted, the shared memory space 2660may be instantiated outside any federated area 2566. However, otherembodiments are possible in which the shared memory space 2660 may beinstantiated within a federated area 2566 to which access has beengranted to a requesting device 2100 or 2800 and/or a user thereof fromwhich a request for a job flow performance was received.

FIGS. 23B-G depict a variety of situations in which conversions of dataobjects 2330, 2370 and/or 2700 between forms thereof may be performedduring the course of an example performance of a job flow. In thisdepicted example, the type of conversion that may be performed includesinstances of serialization and de-serialization. It may be, in thisexample, that the primary programming language in which the executableinstructions 2447 of some of the task routines 2440 are written is onethat supports data objects that are persisted to federated area(s) 2566as structured data arrays (e.g., the SAS programming language), while incontrast, the executable instructions 2447 of others of the taskroutines 2440 are written in a secondary language that supports dataobjects that take an unstructured form such as a list of comma-separatedvalues (CSVs) that is not stored within federated areas 2566 (e.g., aNumPy array for use with Python™).

For sake of ease of reference, executable instructions written in theprimary programming language are designated with the 2447 p referencenumber and their associated task routines are designated with the 2440 preference number, while executable instructions written in the secondaryprogramming language are designated with the 2447 s reference number andtheir associated task routines are designated with the 2440 s referencenumber. Similarly, data objects 2330, 2370 or 2770 that are of ade-serialized form associated with the primary programming language (andare, therefore, of a form that may be stored within a federated area2566 so as to be “persisted” for future analysis) may be designated withthe reference number 2330 p, 2370 p or 2770 p, respectively, while dataobjects 2330, 2370 or 2770 that are of a serialized form associated withthe secondary programming language (and are, therefore, not a form thatis stored within a federated area 2566) may be designated with thereference number 2330 s, 2370 s or 2770 s, respectively.

As depicted throughout FIGS. 23B-G, the performance component 2544 mayincorporate the capability to interpret and/or compile, at runtime,executable instructions 2447 of different task routines that werewritten in different programming languages. More specifically, it may bethat the performance component 2544 incorporates multiple runtimeinterpreters and/or compilers to support the execution of executableinstructions written in each of the primary language and one or moresecondary languages.

Turning to FIG. 23B, as the performance of the example job flowcommences, both a task routine 2440 p with executable instructions 244′7p written in the primary programming language and a task routine 2440 swith executable instructions 2447 s written in the secondary programminglanguage may require the same flow input data set 2330 p as an input. Asdepicted, the flow input data set 2330 p may be retrieved from afederated area 2566, and therefore, may be of a structured formassociated with the primary programming language such that the taskroutine 2440 p is able to directly accept it as an input. However, theflow input data set 2330 p may require some degree of conversion to anunstructured form before it can be provided as an input to the taskroutine 2440 s. The processor(s) 2550 may be caused, at the commencementof the performance of the job flow, to instantiate the depicted sharedmemory space 2660, and may be further caused by the performancecomponent 2544 to serialize the flow input data set 2330 p to generatethe depicted corresponding flow input data set 2330 s within the sharedmemory space 2660 to make the flow input data set 2330 s available tothe task routine 2440 s as an input that is compatible therewith.

As also depicted in FIG. 23B, the processor(s) 2550 may be caused by theperformance component 2544 to execute the executable instructions 2447 pof the task routine 2440 p using a runtime interpreter or compilerappropriate for the primary programming language, and in so doing, maygenerate the depicted mid-flow data set 2370 p. Similarly, theprocessor(s) 2550 may also be caused by the performance component 2544to execute the executable instructions 2447 s of the task routine 2440 susing a runtime interpreter or compiler appropriate for the secondaryprogramming language, and in so doing, may generate the depictedmid-flow data set 2370 s. As suggested by their reference numbers, themid-flow data set 2370 p may be of a structured (de-serialized) formassociated with the primary programming language, while the mid-flowdata set 2370 s may be of an unstructured (serialized) form associatedwith the secondary programming language.

In some embodiments, the opportunity afforded by the form of themid-flow data set 2370 p may be taken to store the mid-flow data set2370 p within a federated area 2566 for future analysis of this job flowperformance for sake of accountability. However, with regard to themid-flow data set 2370 s, it may be deemed more desirable to avoideither storing it in its serialized form or to expend processingresources and time to de-serialize it solely for the purpose of storingit within a federated area. Therefore, unless the mid-flow data set 2370s is de-serialized to prepare it for use as an input to another taskroutine that requires such de-serialization, then the mid-flow data set2370 s may be discarded such that it is not persisted to a federated2566.

Turning to FIG. 23C, it may be that both of the mid-flow data sets 2370p and 2370 s generated in FIG. 23B are used as inputs to another taskroutine 2440 p with executable instructions 2447 p written in theprimary programming language. While the mid-flow data set 2370 p may beable to be provided directly to the other task routine 2440 p as aninput, the mid-flow data set 2370 s may require some degree ofconversion to a structured form before it can be provided as an input tothe other task routine 2440 p. The processor(s) 2550 may be caused bythe performance component 2544 to de-serialize the mid-flow data set2370 s to generate the depicted corresponding mid-flow data set 2370 pthat may be stored within a federated area 2566.

As also depicted in FIG. 23C, the processor(s) 2550 may be caused by theperformance component 2544 to execute the executable instructions 2447 pof the other task routine 2440 p using a runtime interpreter or compilerappropriate for the primary programming language, and in so doing, maygenerate another mid-flow data set 2370 p and/or a result report 2770 p.As suggested by their reference numbers, the mid-flow data set 2370 pand/or result report 2770 p may be of a structured (de-serialized) formassociated with the primary programming language.

Turning to FIG. 23D, as an alternative to what is depicted in FIG. 23C,it may be that both of the mid-flow data sets 2370 p and 2370 sgenerated in FIG. 23B are used as inputs to another task routine 2440 swith executable instructions 2447 s written in the secondary programminglanguage. While the mid-flow data set 2370 s may be able to be provideddirectly to the other task routine 2440 s as an input, the mid-flow dataset 2370 p may require some degree of conversion to a unstructured formbefore it can be provided as an input to the other task routine 2440 s.The processor(s) 2550 may be caused by the performance component 2544 toserialize the mid-flow data set 2370 p to generate the depictedcorresponding mid-flow data set 2370 s that may be stored within sharedmemory space 2660 to enable the task routine 2440 s to access it.

As also depicted in FIG. 23D, the processor(s) 2550 may be caused by theperformance component 2544 to execute the executable instructions 2447 sof the other task routine 2440 s using a runtime interpreter or compilerappropriate for the secondary programming language, and in so doing, maygenerate another mid-flow data set 2370 s and/or a result report 2770 sthat may also be stored in the shared memory space 2660. As suggested bytheir reference numbers, the mid-flow data set 2370 s and/or resultreport 2770 s may be of an unstructured (serialized) form associatedwith the secondary programming language. FIG. 23D also illustrates aninstance of the earlier-described choice to minimize the number ofconversion operations (e.g., serialization and/or de-serializationoperations) that may be performed by refraining from de-serializing themid-flow data set 2370 s that is depicted as being output by the onetask routine 2440 s for use as an input to the other task routine 2440s.

FIG. 23E illustrates an example instance of a single mid-flow data set2370 s stored within the shared memory space 2660 being de-serialized bythe processor(s) 2550 under the control of the performance component2544 to generate a single corresponding mid-flow data set 2370 p, whichmay be stored in a federated area 2566 for sake of future accountabilityand/or used as an input to multiple task routines 2440 p. As alsodepicted, each of the multiple task routines 2440 p may then generateseparate mid-flow data set(s) 2370 p and/or result report(s) 2770 p,each of which may also be stored within a federated area 2566.

FIG. 23F illustrates an alternate example instance of what may be thesame single mid-flow data set 2370 s stored within the shared memoryspace 2660 being provided directly to multiple task routines 2440 s asan input. Again, in such an exchange of a mid-flow data set 2370 ssolely among task routines 2440 s that include executable instructions2447 s written in the secondary programming language, the processor(s)2550 may be caused to refrain from performing serialization for the solepurpose of generating a structured form 2370 p of the mid-flow data set2370 s for storage within a federated area 2566. As also depicted, eachof the multiple task routines 2440 s may then generate separate mid-flowdata set(s) 2370 s and/or result report(s) 2770 s within the sharedmemory space 2660.

FIG. 23G illustrates an example instance of a single mid-flow data set2370 p, that may be stored within a federated area 2566 for sake offuture accountability, being serialized by the processor(s) 2550 underthe control of the performance component 2544 to generate a singlecorresponding mid-flow data set 2370 s stored within the shared memoryspace 2660 to enable it to be used as an input to multiple task routines2440 s. As also depicted, each of the multiple task routines 2440 s maythen generate separate mid-flow data set(s) 2370 s and/or resultreport(s) 2770 s also within the shared memory space 2660.

FIGS. 24A and 24B, together, illustrate an example embodiment of a logicflow 3100. The logic flow 3100 may be representative of some or all ofthe operations executed by one or more embodiments described herein.More specifically, the logic flow 3100 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3110, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a device, via a network (e.g., one of the source devices2100, or one of the reviewing devices 2800, via the network 2999) andthrough a portal provided by the processor for access to other devicesvia the network, to add a new federated area to be connected to aspecified existing federated area. As has been discussed, such a portalmay employ any of a variety of protocols and/or handshake mechanisms toenable the receipt of requests for various forms of access to thefederated area by other devices, as well as to exchange objects withother devices, via the network.

At 3112, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of thespecified federated area (as well as for any related base federated areaand/or any related intervening federated area), and/or has been granteda level of access that includes the authorization to make such requests.Again, the processor may require the receipt of one or more securitycredentials from devices and/or users from which such requests arereceived. If, at 3112, the processor determines that the request is notfrom an authorized device and/or is not from a person and/or entityauthorized as a user with sufficient access to make such a request, thenthe processor may transmit an indication of denial of the request to thedevice from which the request is received via the network at 3114.

However, if at 3112, the processor determines that the request isauthorized, then at 3120, the processor may allocate storage spacewithin the one or more federated devices, and/or within one or morestorage devices under the control of the one or more federated devices,for the requested new federated area that is connected to (e.g.,branches from) the specified existing federated area.

At 3130, the processor may generate a new global federated areaidentifier (GUID) that is to be used to uniquely identify the newfederated area (e.g., a new global federated area identifier 2569). At3132, the processor may add an indication of the creation of therequested new federate area, as well as the manner in which therequested new federated area is connected to the specified existingfederated area to a federated area database that may store indicationsof the existence of each federated area, which users and/or devices aregranted access to each, and/or how each federated area may be connectedor otherwise related to one or more others (e.g., within the portal data2539 and/or the federated area parameters 2536). In so doing, the newfederated area, the specified existing federated area and/or otherfederated areas may be identified and referred to within such databasesby their global federated area identifiers and/or human-readablefederated area identifiers (e.g., the human-readable federated areaidentifiers 2568), with the global federated area identifiers serving toresolve any conflict that may arise among the human-readable federatedarea identifiers).

At 3134, the processor may add an indication to such a database of aninheritance relationship among the new federated area, the specifiedexisting federated area, any base federated area to which the specifiedexisting federated area is related, and any intervening federated areapresent between the specified existing federated area and the basefederated area. As has been discussed, with such an inheritancerelationship in place, any object stored within any base federated areato which the specified existing federated area may be related, withinthe specified existing federated, and/or within any interveningfederated area that may be present between the specified existingfederated area and such a base federated area may become accessible fromwithin the new federated area as if stored within the new federatedarea.

At 3136, the processor may add an indication to such a database of apriority relationship among the new federated area, the specifiedexisting federated area, any base federated area to which the specifiedexisting federated area is related, and any intervening federated areapresent between the specified existing federated area and the basefederated area. As has been discussed, with such a priority relationshipin place, the use of objects stored within the new federated area isgiven priority over the use of similar objects (e.g., other taskroutines 2440 that perform the same task) that may be stored within anybase federated area to which the specified existing federated area maybe related, within the specified existing federated, and/or within anyintervening federated area that may be present between the specifiedexisting federated area and such a base federated area.

At 3140, the processor may check whether there is at least one otherexisting federated area that is connected to the requested new federatedarea within a set of related federated areas such that it is to have atleast an inheritance relationship with the requested new federated areasuch that it is to inherit objects from the requested new federatedarea. As has been discussed, this may occur where the requested newfederated area is requested to be instantiated at a position within alinear hierarchy or within a branch of a hierarchical tree such that itis interposed between two existing federated areas.

If, at 3140, there is such another federated area, then at 3142, theprocessor may add an indication to such a database of an inheritancerelationship among the other existing federated area, the requested newfederated area, the specified existing federated area, any basefederated area to which the specified existing federated area and theother federated area are related, and any intervening federated areapresent between the specified existing federated area and the basefederated area. In this way, any object stored within any base federatedarea, within the specified existing federated, within any interveningfederated area that may be present between the specified existingfederated area and such a base federated area, or within the requestednew federated area may become accessible from within the other existingfederated area as if stored within the other existing federated area.

At 3144, the processor may add an indication to such a database of apriority relationship among the other existing federated area, therequested new federated area, the specified existing federated area, anybase federated area to which the specified existing federated area isrelated, and any intervening federated area present between thespecified existing federated area and the base federated area. In thisway, the use of objects stored within the other existing federated areais given priority over the use of similar objects (e.g., other taskroutines 2440 that perform the same task) that may be stored within therequested new federated area, any base federated area to which thespecified existing federated area may be related, within the specifiedexisting federated, and/or within any intervening federated area thatmay be present between the specified existing federated area and such abase federated area.

FIGS. 25A, 25B, 25C, 25D, 25E and 25F, together, illustrate an exampleembodiment of a logic flow 3200. The logic flow 3200 may berepresentative of some or all of the operations executed by one or moreembodiments described herein. More specifically, the logic flow 3200 mayillustrate operations performed by the processor(s) 2550 in executingthe control routine 2540, and/or performed by other component(s) of atleast one of the federated devices 2500.

At 3210, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from another device, via a network (e.g., one of the sourcedevices 2100, or one of the reviewing devices 2800, via the network2999) and through a portal provided by the processor for access to otherdevices via the network, to store one or more objects (e.g., one or moreof the objects 2220, 2270, 2330, 2370, 2440, 2470, 2720 and/or 2770)within a specified federated area (e.g., one of the federated areas2566). As has been discussed, such a portal may employ any of a varietyof protocols and/or handshake mechanisms to enable the receipt ofrequests for various forms of access to a federated area by otherdevices, as well as to exchange objects with other devices, via thenetwork.

At 3212, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the other device that is an authorized userof the specified federated area, and/or has been granted a level ofaccess that includes the authorization to make such requests. As hasbeen discussed, the processor may require the receipt of one or moresecurity credentials from devices from which requests are received. If,at 3212, the processor determines that the request is not from a deviceand/or user authorized to make such a request, then the processor maytransmit an indication of denial of the request to the device via thenetwork at 3214.

However, if at 3212, the processor determines that the request to storeone or more objects within the specified federated area is authorized,then at 3220, the processor may check whether the one or more objectsincludes one or more data sets (e.g., one or more of the flow input datasets 2330 and/or one or more mid-flow data sets 2370). If so, then theprocessor may generate and assign a data object identifier for each dataset that is to be stored (e.g., one or more of the data objectidentifiers 3331) at 3222. At 3224, the processor may store each of theone or more data sets within the specified federated area.

At 3230, the processor may check whether the one or more objectsincludes one or more result reports (e.g., one or more of the resultreports 2770). If so, then the processor may generate and assign aresult report identifier for each result report that is to be stored(e.g., one or more of the result report identifiers 2771) at 3232. At3234, the processor may store each of the one or more result reportswithin the specified federated area.

At 3240, the processor may check whether the one or more objectsincludes one or more task routines (e.g., one or more of the taskroutines 2440). If so, then the processor may generate and assign a taskroutine identifier for each task routine that is to be stored (e.g., oneor more of the task routine identifiers 2441) at 3242. At 3244, theprocessor may store each of the one or more task routines within thespecified federated area. At 3246, the processor may additionally checkwhether any of the task routines stored at 3244 have the same flow taskidentifier as another task routine that was already stored within thespecified federated area (or within any base federated area to which thespecified federated area is related and/or within any interveningfederated area interposed therebetween), such that there is more thanone task routine executable to perform the same task. If so, then at3248 for each newly stored task routine that shares a flow taskidentifier with at least one other task routine already stored in thespecified federated area (or within such a base or intervening federatedarea), the processor may store an indication of there being multipletask routines with the same flow task identifier, along with anindication of which is the most recent of the task routines for thatflow task identifier.

As has been discussed, in embodiments in which task routines are storedin a manner organized into a database or other data structure (e.g., thetask routine database 2564 within one or more related federated areas)by which flow task identifiers may be employed as a mechanism to locatetask routines, the storage of an indication of there being more than onetask routine sharing the same flow task identifier may entailassociating more than one task routine with the same flow taskidentifier so that a subsequent search for task routines using that flowtask identifier will beget a result indicating that there is more thanone. As has also been discussed, the manner in which one of multipletask routines sharing the same flow task identifier may be indicated asbeing the most current version may entail ordering the manner in whichthose task routines are listed within the database (or other datastructure) to cause the most current one to be listed at a particularposition within that order (e.g., listed first).

At 3250, the processor may check whether the one or more objectsincludes one or more macros (e.g., one or more of the macros 2470). Ifso, then at 3252, the processor may additionally check, for each macro,whether there is a corresponding task routine (or corresponding multipleversions of a task routine in embodiments in which a single macro may bebased on multiple versions) stored within the specified federated area(or within any base federated area to which the specified federated areais related and/or within any intervening federated area interposedtherebetween). If, at 3252, there are any macros requested to be storedfor which there is a corresponding task routine (or correspondingmultiple versions of a task routine) stored in the specified federatedarea (or within such a base or intervening federated area), then foreach such macro, the processor may assign the job flow identifier (e.g.,one or more of the job flow identifiers 2221) of the corresponding taskroutine (or may assign job flow identifiers of each of the versions of atask routine) at 3254. At 3256, the processor may store each of suchmacros.

At 3260, the processor may check whether the one or more objectsincludes one or more job flow definitions (e.g., one or more of the jobflow definitions 2220). If so, then at 3262, the processor mayadditionally check, for each job flow definition, whether that job flowdefinition defines a job flow that uses a neural network and was trainedand/or tested using objects associated with another job flow (and/orperformances thereof) that is defined to by its job flow definition tonot use a neural network. As previously discussed, the preservation ofsuch links between a neuromorphic job flow and an earliernon-neuromorphic job flow from which the neuromorphic job flow may be insome way derived may be of importance to ensuring accountability duringa later evaluation of the neuromorphic job flow. For this reason, it maybe deemed important to ensure that objects associated with the othernon-neuromorphic job flow have already been stored in federated area(s)where they can be preserved for subsequent retrieval during such anevaluation of the neuromorphic job flow.

Presuming that there are no neuromorphic job flows requested to bestored that were derived from another non-neuromorphic job flow that isnot already so stored, then at 3264, the processor may additionallycheck, for each job flow definition, whether there is at least one taskroutine stored within the specified federated area (or within any basefederated area to which the specified federated area is related and/orwithin any intervening federated area interposed therebetween) for eachtask specified by a flow task identifier within the job flow definition.If, at 3264, there are any job flow definitions requested to be storedfor which there is at least one task routine stored in the specifiedfederated area (or within such a base or intervening federated area) foreach task, then for each of those job flow definitions where there is atleast one stored task routine for each task, the processor may generateand assign a job flow identifier (e.g., one or more of the job flowidentifiers 2221) at 3267, and at 3269, may then store each of the oneor more job flow definitions for which there was at least one taskroutine for each task. Otherwise, at 3265, for each job flow for whichthere is no task routine stored for one or more tasks, the processor maygenerate a DAG (e.g., one of the DAGs 2270) that provides a visualindication of the lack of task routines for each such task, and maytransmit the DAG to the other device.

At 3270, the processor may check whether the one or more objectsincludes one or more instance logs (e.g., one or more of the instancelogs 2720). If so, then at 3272, the processor may additionally check,for each instance log, whether each object identified in the instancelog by its identifier is stored within the specified federated area (orwithin any base federated area to which the specified federated area isrelated and/or within any intervening federated area interposedtherebetween). If, at 3272, there are any instance logs requested to bestored for which each specified object is stored within the specifiedfederated area (or within such a base or intervening federated area),then for each instance log where each object specified therein is sostored, the processor may generate and assign an instance log identifier(e.g., one or more of the instance log identifiers 2721) at 3275, and at3277, may then store each of the one or more instance logs for whicheach specified object is so stored. Otherwise, at 3273, for eachinstance log for which there is an identified object that is not stored,the processor may generate a DAG that provides a visual indication ofeach such missing object, and may transmit the DAG to the other device.

At 3280, the processor may check whether the one or more objectsincludes one or DAGs. If so, then at 3282, the processor mayadditionally check, for each DAG, whether there is a corresponding taskroutine (or corresponding multiple versions of a task routine) for eachtask graph object (e.g., one of the task graph objects 2984) and whetherthere is a corresponding data object for each data graph object (e.g.,each data graph object 2983 or 2987) stored within the specifiedfederated area (or within any base federated area to which the specifiedfederated area is related and/or within any intervening federated areainterposed therebetween). If, at 3282, there are any of such DAGs to bestored in the specified federated area (or within such a base orintervening federated area) for which all of such task routines and dataobjects are so stored, then for each of such DAG, the processor maygenerate and assign a job flow identifier at 3285 in recognition of thepossibility that such a DAG may be used as a new job flow definition,and at 3286, may then store each of such DAGs. Otherwise, at 3265, foreach job flow for which there is no task routine stored for one or moretasks, the processor may generate a DAG (e.g., one of the DAGs 2270)that provides a visual indication of the lack of task routines for eachsuch task, and may transmit the DAG to the other device. Otherwise, at3283, for each DAG for which there is a task routine and/or a dataobject that is not stored, the processor may generate another DAG thatprovides a visual indication of each such missing object, and maytransmit the other DAG to the other device.

FIGS. 26A, 26B and 26C, together, illustrate an example embodiment of alogic flow 3300. The logic flow 3300 may be representative of some orall of the operations executed by one or more embodiments describedherein. More specifically, the logic flow 3300 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3310, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a device, via a network (e.g., one of the source devices2100, or one of the reviewing devices 2800, via the network 2999) andthrough a portal provided by the processor for access to other devicesvia the network, to store a task routine (e.g., one of the task routines2440) within a particular federated area specified in the request (e.g.,one of the federated areas 2566). Again, such a portal may be generatedby the processor to employ any of a variety of protocols and/orhandshake mechanisms to enable the receipt of requests for various formsof access to the federated area by other devices, as well as to exchangeobjects with other devices, via the network. Alternatively, at 3310, theprocessor may receive the task routine, via the network, and in atransfer associated with a synchronization relationship between atransfer area instantiated within the particular federated area andanother transfer area instantiated within the other device, where thetask routine is intended to be stored within the transfer area withinthe particular federated area.

At 3312, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request or synchronization relationship transferis from an authorized device and/or from an authorized person or entity(e.g., scholastic, governmental or business entity) operating the devicethat is an authorized user of the specified federated area. As has beendiscussed, the processor may require the receipt of one or more securitycredentials from devices from which requests are received and/or withwhich transfers of objects associated with synchronization relationshipsare performed. If, at 3312, the processor determines that there is nosuch authorization, then the processor may transmit an indication ofdenial of the storage of the task routine to the other device via thenetwork at 3314.

However, if at 3312, the processor determines that there is suchauthorization, then at 3320, the processor may check whether the taskroutine has the same flow task identifier as any of the task routinesalready stored within the particular federated area (or within any basefederated area to which the specified federated area is related and/orwithin any intervening federated area interposed therebetween), suchthat there is already stored one or more other task routines executableto perform the same task. If not at 3320, then the processor maygenerate and assign a task routine identifier for the task routine(e.g., one of the task routine identifiers 2441) at 3322. At 3324, theprocessor may store the task routine within the particular federatedarea in a manner that enables later retrieval of the task routine byeither its identifier or by the flow task identifier of the task that itperforms.

However, if at 3320, there is at least one other task routine with thesame flow task identifier already stored within the particular federatedarea (or within such a base or intervening federated area), then at3330, the processor may translate the portions of executableinstructions within each of these task routines that implement the inputand/or output interfaces to generate intermediate representation(s) ofthe input and/or output interfaces for each of these task routines. Ashas been discussed, it may be that different ones of these task routinesare written in different programming languages, which may make directcomparisons of implementations of input and/or output interfacesrelatively difficult, and it may be that the intermediaterepresentations generated for each include executable instructionsgenerated in an intermediate programming language to better facilitatesuch direct comparisons. Alternatively or additionally, the intermediaterepresentations may include a data structure of various values forvarious parameters of input and/or output interfaces that better enablesuch direct comparisons. At 3332, the processor may perform suchcomparisons using the intermediate representations.

Based on the results of those comparisons, the processor may check at3340: 1) whether the input interfaces (e.g., data interfaces 2443 thatreceive data from data objects, and/or task interfaces 2444 that receiveparameters from another task routine) are implemented in the taskroutine in a manner that is identical to those of the one or more othertask routines with the same flow task identifier that are already sostored, and 2) whether the output interfaces (e.g., data interfaces 2443that output a data object, and/or task interfaces 2444 that outputparameters to another task routine) are implemented in the task routinein a manner that is either identical to or a superset of those of theone or more task routines with the same flow task identifier that arealready stored within the federated area (or within such a base orintervening federated area). If at 3340, the input interfaces areidentical, and each of the output interfaces of the task routine isidentical to or a superset of the corresponding output interface withinthe one or more other task routine(s) already stored within thefederated area (or within such a base or intervening federated area),then the processor may generate and assign a task routine identifier forthe task routine at 3350. At 3352, the processor may store the taskroutine within the specified federated area in a manner that enableslater retrieval of the task routine by either its identifier or by theflow task identifier of the task that it performs. At 3354, theprocessor may also store an indication of there being multiple taskroutines with the same flow task identifier, along with an indication ofwhich is the most recent of the task routines for that flow taskidentifier.

However, if at 3340, the input interfaces are not identical, or theoutput interface(s) of the task routine are neither identical nor asuperset, then at 3342, the processor may generate a DAG (e.g., one ofthe DAGs 2270) that provides a visual indication of the mismatch, andmay transmit the DAG to the other device. If, at 3344, the task routinewas received in a transfer from the other device as a result of asynchronization relationship, then the processor may proceed with theassignment of a task routine identifier at 3350, followed by storage ofthe task routine, etc. As has been discussed, proceeding with thestorage of the task routine in spite of such a mismatch inimplementations of input and/or output interfaces may be deemeddesirable as it results in the synchronization relationship between thetwo transfer areas being maintained such that the contents of the twotransfer areas are caused to be synchronized with each other. It may bedeemed sufficient that the DAG providing a visualization of the detailsof the mismatch is generated and provided to the other device as amechanism to notify the developer(s) who created the task routine sothat they are able to correct it.

FIGS. 27A, 27B and 27C, together, illustrate an example embodiment of alogic flow 3400. The logic flow 3400 may be representative of some orall of the operations executed by one or more embodiments describedherein. More specifically, the logic flow 3400 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3410, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from another device, via a network (e.g., one of the sourcedevices 2100, or one of the reviewing devices 2800, via the network2999) and through a portal provided by the processor for access to otherdevices via the network, to store a job flow definition (e.g., one ofthe job flow definitions 2220) within a particular federated areaspecified within the request (e.g., one of the federated areas 2566).Alternatively, at 3410, the processor may receive the job flowdefinition, via the network, and in a transfer associated with asynchronization relationship between a transfer area instantiated withinthe particular federated area and another transfer area instantiatedwithin the other device, where the job flow definition is intended to bestored within the transfer area within the particular federated area.

At 3412, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of thespecified federated area, and/or has been granted a level of access thatincludes the authorization to make such requests. As has been discussed,the processor may require the receipt of one or more securitycredentials from devices from which requests are received. If, at 3412,the processor determines that the request is not from a device and/oruser authorized to make such a request, then the processor may transmitan indication of denial of the storage of the job flow definition to thedevice via the network at 3414.

However, if at 3412, the processor determines that the request to storea job flow definition within the specified federated area is authorized,then at 3420, the processor may check whether the job flow of the jobflow definition uses a neural network that was trained based on anotherjob flow that does not use a neural network. If, at 3420, the processordetermines that the job flow of the job flow definition does not use aneural network, or if at 3422, the processor determines that the otherjob flow definition is stored in the particular federated area (orwithin any base federated area to which the particular federated area isrelated and/or within any intervening federated area interposedtherebetween), then at 3430, the processor may check whether there is atleast one task routine stored within the federated area (or within anysuch base or such intervening federated area) for each task specified bya flow task identifier within the job flow definition.

However, if at 3420, the processor determines that the job flow of thejob flow definition does use a neural network, and if at 3422, the otherjob flow definition is not so stored, then at 3424, the processor maycheck whether the job flow definition was received in a transfer fromthe other device as a result of a synchronization relationship. If notthen, the processor may transmit an indication of denial of the storageof the job flow definition to the other device via the network at 3414.Otherwise, the processor may transmit an indication of an error arisingfrom the other job flow definition not being so stored at 3426, beforeproceeding to the check made at 3430.

If, at 3430, there is at one task routine stored in the particularfederated area (or within any base federated area to which theparticular federated area is related and/or within any interveningfederated area interposed therebetween) for each of the tasks specifiedby the job flow, then the processor may proceed to another check made at3440. However, if at 3430, there are no task routines stored within thefederated area (or within such a base or intervening federated area) forone or more of the tasks specified by the job flow, then at 3432, theprocessor may generate a DAG that provides a visual depiction of thelack of task routines for one or more tasks, and may transmit it to theother device. Then, if at 3434, the job flow definition was received ina transfer from the other device as a result of a synchronizationrelationship, the processor may proceed to the check made at 3440.

At 3440, the processor may check: 1) whether the input interfaces (e.g.,data interfaces 2443 that receive data from data objects, and/or taskinterfaces 2444 that receive parameters from another task routine) thatare implemented in the task routines stored in the federated area (orwithin such a base or intervening federated area) are identical to thosespecified in the job flow definition at 3440, and 2) whether the outputinterfaces (e.g., data interfaces 2443 that output a data object, and/ortask interfaces 2444 that output parameters to another task routine)that are implemented in the task routines that are already stored withinthe federated area (or within such a base or intervening federated area)are identical to or are supersets of those specified in the job flowdefinition.

If at 3440, the input interfaces are identical, and if all of the outputinterfaces of all of the task routines already so stored are eitheridentical to and/or are supersets of corresponding output interfacesspecified in the job flow definitions, then the processor may generateand assign a job flow identifier for the job flow definition at 3446,and at 3448, may store the job flow definition within the particularfederated area in a manner that enables later retrieval of the job flowby its identifier.

However, if at 3340, the input interfaces are not identical, or if anoutput interface of one or more of the task routines already so storedis neither identical nor a superset of a corresponding output interfacespecified in the job flow definition, then at 3442, the processor maygenerate a DAG that provides a visual indication of the mismatch, andmay transmit it to the other device via the network. If, at 3444, thejob flow definition was received in a transfer from the other device asa result of a synchronization relationship, the processor may proceed tothe generation and transmission of a DAG at 3446.

FIGS. 28A, 28B, 28C and 28D, together, illustrate an example embodimentof a logic flow 3500. The logic flow 3500 may be representative of someor all of the operations executed by one or more embodiments describedherein. More specifically, the logic flow 3500 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3510, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a device, via a network (e.g., one of the source devices2100, or one of the reviewing devices 2800, via the network 2999) andthrough a portal provided by the processor, to delete one or moreobjects (e.g., one or more of the objects 2220, 2330, 2370, 2440, 2720and/or 2770) within a particular federated area specified in the request(e.g., one of the federated areas 2566).

At 3512, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of thespecified federated area, as well as any federated area that may branchfrom the specified federated area, and/or has been granted a level ofaccess that includes the authorization to make such requests. As hasbeen discussed, the processor may require the receipt of one or moresecurity credentials from devices from which requests are received. If,at 3512, the processor determines that the request is not from a deviceand/or user authorized to make such a request, then the processor maytransmit an indication of denial of the request to the device via thenetwork at 3514.

However, if at 3512, the processor determines that the request to deleteone or more objects within the specified federated area is authorized,then at 3520, the processor may check whether the one or more objectsincludes one or more data sets (e.g., one or more of the data sets 2330or 2370). If so, then the processor may delete the one or more data setsfrom the specified federated area at 3522. At 3524, the processor mayadditionally check whether there are any result reports or instance logsstored in the specified federated area (or within any federated areathat branches from the specified federated area) that were generated ina past performance of a job flow in which any of the one or more deleteddata sets were used. If so, then at 3526, the processor may delete suchresult report(s) and/or instance log(s) from the specified federatedarea and/or from one or more other federated areas that branch from thespecified federated area.

As previously discussed, it may be deemed desirable for reasons ofmaintaining repeatability to avoid a situation in which there is aninstance log that specifies one or more objects, such as data sets, asbeing associated with a performance of a job flow where the one or moreobjects are not present within any accessible federated area such thatthe performance of the job flow cannot be repeated. It is for thisreason that the deletion of a data set from the specified federated areais only to be performed if a check can be made within federated areasthat branch from the specified federated area for such objects asinstance logs and/or result reports that have such a dependency on thedata set to be deleted. And, it is for this reason that a request forsuch a deletion may not be deemed to be authorized unless received froma device and/or user that has authorization to access all of thefederated areas that branch from the specified federated area.

At 3530, the processor may check whether the one or more objectsincludes one or more result reports (e.g., one or more of the resultreports 2770). If so, then the processor may delete the one or moreresult reports from the specified federated area at 3532. At 3534, theprocessor may additionally check whether there are any instance logsstored in the specified federated area (or within any federated areathat branches from the specified federated area) that were generated ina past performance of a job flow in which any of the one or more deletedresult reports were generated. If so, then at 3536, the processor maydelete such instance log(s) from the federated area and/or from the oneor more other federated areas that branch from the specified federatedarea.

At 3540, the processor may check whether the one or more objectsincludes one or more task routines (e.g., one or more of the taskroutines 2440). If so, then the processor may delete the one or moretask routines from the specified federated area at 3542. At 3544, theprocessor may additionally check whether there are any other taskroutines stored in the specified federated area (or within a federatedarea that branches from the specified federated area) that share thesame flow task identifier(s) as any of the deleted task routines. If so,then at 3546, the processor may delete such task routine(s) from thespecified federated area and/or from the one or more other federatedareas that branch from the specified federated area. At 3550, theprocessor may additionally check whether there are any result reports orinstance logs stored in the specified federated area (or within afederated area that branches from the specified federated area) thatwere generated in a past performance of a job flow in which any of theone or more deleted task routines were used. If so, then at 3552, theprocessor may delete such result report(s) and/or instance log(s) fromthe specified federated area and/or from the one or more other federatedareas that branch from the specified federated area.

At 3560, the processor may check whether the one or more objectsincludes one or more job flow definitions (e.g., one or more of the jobflow definitions 2220). If so, then at 3562, the processor may deletethe one or more job flow definitions within the specified federatedarea. At 3564, the processor may additionally check whether there areany result reports or instance logs stored in the specified federatedarea (or within a federated area that branches from the specifiedfederated area) that were generated in a past performance of a job flowdefined by any of the one or more deleted job flow definitions. If so,then at 3566, the processor may delete such result report(s) and/orinstance log(s) from the federated area and/or from the one or moreother federated areas that branch from the specified federated area.

At 3570, the processor may check whether the one or more objectsincludes one or more instance logs (e.g., one or more of the instancelogs 2720). If so, then at 3572, the processor may delete the one ormore instance logs from the specified federated area.

FIGS. 29A and 29B, together, illustrate an example embodiment of a logicflow 3600. The logic flow 3600 may be representative of some or all ofthe operations executed by one or more embodiments described herein.More specifically, the logic flow 3600 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3610, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a device, via a network (e.g., one of the reviewing devices2800 via the network 2999) and through a portal provided by theprocessor, to repeat a previous performance of a job flow that generatedeither a result report or an instance log (e.g., one of the resultreports 2770 or one of the instance logs 2720) specified in the request(e.g., with a result report identifier 2771 or an instance logidentifier 2721), or to provide the requesting device with the objects(e.g., one or more of the objects 2220, 2330, 2370, 2440, 2720 and/or2770) needed to enable the requesting device to do so. As previouslydiscussed, persons and/or entities involved in peer reviewing and/orother forms of review of analyses may operate a device to make a requestfor one or more federated devices to repeat a performance of a job flowto verify an earlier performance, or may make a request for the objectsneeded to allow the persons and/or entities to independently repeat theperformance.

At 3612, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of atleast one federated area, and/or has been granted a level of access thatincludes the authorization to make such requests. As has been discussed,the processor may require the receipt of one or more securitycredentials from devices from which requests are received. If, at 3612,the processor determines that the request is not from a device and/oruser authorized to make such a request, then the processor may transmitan indication of denial of the request to the requesting device via thenetwork at 3614.

However, if at 3612, the processor determines that the request isauthorized, then at 3620, if the a result report was specified for theprevious performance in the request, instead of the instance log, thenat 3622, the processor may the use the result report identifier providedin the request for the result report to retrieve the instance log forthe previous performance. Alternatively, if the instance log wasspecified for the previous performance in the request, then at 3624, theprocessor may use the instance log identifier provided in the request toretrieve the instance log for the previous performance.

At 3630, regardless of the exact manner in which the instance log isretrieved, the processor may use the identifiers specified in theinstance log for the objects associated with the previous performance toretrieve each of those objects. It should be noted that, as has beenpreviously discussed, searches for objects to fulfill such a requestreceived from a particular requesting device may be limited to the oneor more federated areas to which that particular requesting deviceand/or a user operating the requesting device has been granted access(e.g., a particular private or intervening federated area, as well asany base federated area and/or any other intervening federated areainterposed therebetween). Therefore, the retrieval of objects used inthe previous performance, and therefore, needed again to independentlyregenerate the result report, may necessarily be limited to suchauthorized federated area(s).

At 3632, the processor may check whether the job flow relies on the useof a neural network that was trained using one or more performances ofanother job flow that does not relay on the use of a neural network. Ifso, then at 3634, the processor may use an identifier in either of thejob flow definition or instance log retrieved for the previousperformance that provides a link to the job flow definition or instancelog of the other job flow to retrieve objects associated with the otherjob flow and/or one or more performances of the other job flow.

Regardless of whether the job flow of the previous performance referredto in the request relies on the use of a neural network, if, at 3640,the request was to provide the objects needed to enable an independentrepeat of the previous performance of the job flow referred to in therequest, then at 3642, the processor may transmit the retrieved objectsassociated with that previous performance to the requesting device to soenable such an independent repeat performance. As previously discussed,the regenerated result report may be compared at the requesting deviceto the result report that was previously generated during the previousperformance to verify one or more aspects of the previous performance.However, if at 3640, the request received was not to so provide theretrieved objects, but instead, was for one or more federated devices torepeat the previous performance of the job flow, then at 3650, theprocessor may employ the objects retrieved at 3630 to repeat theprevious performance, and thereby regenerate the result report. Aspreviously discussed, in some embodiments, including embodiments inwhich one or more of the data sets associated with the previousperformance is relatively large in size, the processor of the federateddevice may cooperate with the processors of multiple other federateddevices (e.g., operate as the federated device grid 1005) to portions ofthe repeat performance among multiple federate devices to be carried outat least partially in parallel. At 3652, the processor may compare theregenerated result report to the result report previously generated inthe previous performance of the job flow. The processor may thentransmit the results of that comparison to the requesting device at3654.

However, if, at 3632, the job flow of the previous performance referredto in the request does rely on the use of a neural network, then, inaddition to retrieving objects associated with the other job flow at3634, the processor may check at 3660 whether the request was to providethe objects needed to enable an independent repeat of the previousperformance. If so, then at 3662, the processor may transmit theretrieved objects associated with that other job flow to the requestingdevice to enable aspects of the other job flow and/or one or moreperformances thereof to also be evaluated. However, if at 3660, therequest received was not to so provide the retrieved objects, butinstead, was for one or more federated devices to repeat the previousperformance of the job flow, then at 3670, the processor may employ theobjects retrieved at 3634 to perform the other job flow, and do so withthe data set(s) associated with the previous performance of the job flowreferred to in the request. At 3672, the processor may compare theresult report(s) generated by the performance of the other job flow tothe corresponding result reports regenerated from the repetition at 3650of the previous performance of the job flow referred to in the request.The processor may then transmit the results of that comparison to therequesting device at 3674.

FIGS. 30A and 30B, together, illustrate an example embodiment of a logicflow 3700. The logic flow 3700 may be representative of some or all ofthe operations executed by one or more embodiments described herein.More specifically, the logic flow 3700 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3710, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a requesting device, via a network (e.g., one of thereviewing devices 2800 via the network 2999) and through a portalprovided by the processor, to repeat a previous performance a job flowwith one or more data sets (e.g. one or more of the flow input data sets2330) specified in the request by a job flow identifier and one or moredata object identifiers (e.g., one of the job flow identifiers 2221, andone or more of the data object identifiers 2331). As previouslydiscussed, persons and/or entities involved either in consuming resultsof analyses or in reviewing past performances of analyses may operate adevice to make a request for one or more federated devices to repeat aperformance of a job flow.

At 3712, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of atleast one federated area, and/or has been granted a level of access thatincludes the authorization to make such requests. As has been discussed,the processor may require the receipt of one or more securitycredentials from devices from which requests are received. If, at 3712,the processor determines that the request is not from a device and/oruser authorized to make such a request, then the processor may transmitan indication of denial of the request to the device via the network at3714.

However, if at 3712, the processor determines that the request for arepeat of a performance of the specified job flow with the specified oneor more data sets is authorized, then at 3720, the processor may the usethe combination of the job flow identifier and the one or more dataobject identifiers to search within one or more federated areas to whichthe requesting device and/or a user of the requesting device has beengranted access for an instance log associated with a previousperformance of the job flow with the one or more data sets.

It should be noted that, as has been previously discussed, searches forobjects to fulfill such a request received from a requesting device maybe limited to the one or more federated areas to which that requestingdevice and/or a user operating the requesting device has been grantedaccess (e.g., a particular private or intervening federated area, aswell as any base federated area and/or any other intervening federatedarea interposed therebetween). Therefore, the retrieval of objectsneeded to repeat a previous performance of a job flow may necessarily belimited to such authorized federated area(s).

If, at 3730, the processor determines, as a result of the search at3720, that there is no such instance log, then at 3732, the processormay retrieve the job flow definition specified by the job flowidentifier provided in the request (e.g., one of the job flowdefinitions 2220) from the one or more federated areas for whichauthorization to access has been granted to the requesting device and/orthe user of the requesting device. At 3734, the processor may thenretrieve the most recent version of task routine for each task specifiedin the job flow definition by a flow task identifier (e.g., one or moreof the task routines 2440, each specified by a flow task identifiers2241) from the one or more federated areas to which access has beengranted. At 3736, the processor may retrieve each of the one or moredata sets specified by the one or more data object identifiers from theone or more federated areas to which access has been granted, and maythen use the retrieved job flow definition, the retrieved newestversions of task routines, and the retrieved one or more data sets toperform the job flow as requested. At 3738, the processor may transmitthe results of the performance to the requesting device. As analternative to (or in addition to) performing the job flow with the mostrecent versions of the task routines, the processor may transmit anindication to the requesting device that no record has been found of aprevious performance in the one or more federated areas to which accesshas been granted.

However, if at 3730, the processor successfully locates (during thesearch at 3720) such an instance log, then the processor mayadditionally determine at 3740 whether there is more than one suchinstance log, each of which is associated with a different performanceof the job flow with the one or more data sets specified in the request.If, at 3740, only one such instance log was located during the search at3720, then at 3750, the processor may then retrieve the versionsspecified in the instance log of each of the task routines specified inthe job flow definition for each task by a flow task identifier from theone or more federated areas to which access has been granted. At 3752,the processor may retrieve each of the one or more data sets specifiedby the one or more data object identifiers from the one or morefederated areas to which access has been granted, and may then use theretrieved job flow definition, the retrieved specified versions of taskroutines, and the retrieved one or more data sets to perform the jobflow as requested. At 3754, the processor may additionally retrieve theresult report generated in the previous performance of the job flow fromthe one or more federated areas to which access has been granted, andmay compare the retrieved result report to the new result reportgenerated in the new performance of the job flow at 3756. At 3758, theprocessor may transmit the results of the comparison of result reportsto the requesting device, and may transmit the new result report,itself, to the requesting device at 3758.

However, if at 3740, there is more than one such instance log locatedfound during the search at 3720, then the processor may transmit anindication of the available selection of the multiple previousperformances that correspond to the multiple located instance logs tothe requesting device at 3742 with a request that one of the multipleprevious performances be selected as the one from which the instance logwill be used. The processor may then await receipt of an indication of aselection of one of the multiple previous performances at 3744 beforeproceeding to retrieve specific versions of task routines at 3750.

FIGS. 31A, 31B, 31C and 31D, together, illustrate an example embodimentof a logic flow 3800. The logic flow 3800 may be representative of someor all of the operations executed by one or more embodiments describedherein. More specifically, the logic flow 3800 may illustrate operationsperformed by the processor(s) 2550 in executing the control routine2540, and/or performed by other component(s) of at least one of thefederated devices 2500.

At 3810, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a device, via a network (e.g., one of the reviewing devices2800 via the network 2999) and through a portal provided by theprocessor, to perform a job flow with one or more data sets (e.g. one ormore of the flow input data sets 2330) specified in the request by a jobflow identifier and one or more data object identifiers (e.g., one ofthe job flow identifiers 2221, and one or more of the data objectidentifiers 2331).

At 3812, in embodiments in which the federated device(s) that providefederated area(s) also control access thereto, the processor may performa check of whether the request is from an authorized device and/or froman authorized person or entity (e.g., scholastic, governmental orbusiness entity) operating the device that is an authorized user of atleast one federated area, and/or has been granted a level of access thatincludes the authorization to make such requests. As has been discussed,the processor may require the receipt of one or more securitycredentials from devices from which requests are received. If, at 3812,the processor determines that the request is not from a device and/oruser authorized to make such a request, then the processor may transmitan indication of denial of the request to the device via the network at3814.

However, if at 3812, the processor determines that the request for aperformance of the specified job flow with the specified one or moredata sets is authorized, then at 3820, the processor may the use the jobflow identifier provided in the request to retrieve the correspondingjob flow definition (e.g., one of the job flow definitions 2220) fromwithin one or more federated areas to which the requesting device and/ora user of the requesting device has been granted access. At 3822, theprocessor may then retrieve the most recent version of task routine foreach task specified in the job flow definition by a flow task identifier(e.g., one or more of the task routines 1440, each specified by a flowtask identifiers 1241) that is stored within the one or more federatedareas to which the requesting device and/or a user of the requestingdevice has been granted access.

It should be noted that, as has been previously discussed, searches forobjects to fulfill such a request received from a particular device maybe limited to the one or more federated areas to which that requestingdevice and/or a user operating the requesting device has been grantedaccess (e.g., a particular private or intervening federated area, aswell as any base federated area and/or any other intervening federatedarea interposed therebetween). Therefore, the retrieval of objectsneeded to perform a specified job flow may necessarily be limited tosuch authorized federated area(s).

At 3824, the processor may use the combination of the job flowidentifier and the one or more data object identifiers to search for aninstance log associated with a previous performance of the job flow withthe one or more data sets within the one or more federated areas towhich the requesting device and/or a user of the requesting device hasbeen granted access. If, at 3830, the processor determines (during thesearch at 3824) that there is no such instance log, then at 3832, theprocessor may then check whether all of the retrieved newest versions oftask routines are written in the same programming language. As has beendiscussed, there may be an expectation that, normally, task routines areall written in a single primary programming language that is normallysupported for executing the executable instructions within task routines(e.g., the executable instructions 2447). However, as has also beendiscussed, it may be that there is a mixture of two or more programminglanguages (e.g., the primary programming language along with one or moresecondary programming languages) among a set of task routines to beexecuted in performing the tasks of a job flow.

If, at 3832, all of the retrieved most recent versions of task routinesare written in the same programming language (e.g., the primaryprogramming language), then at 3834, the processor may retrieve each ofthe one or more data sets specified by the one or more data objectidentifiers from the one or more federated areas to which the requestingdevice and/or a user of the requesting device has been granted access,and may then use the retrieved job flow definition, the retrieved newestversions of task routines, and the retrieved one or more data sets toperform the job flow as requested. In so doing, the processor may becaused to use the same runtime interpreter or compiler to execute theexecutable instructions within all of the retrieved most recent versionsof task routines. At 3838, the processor may then transmit the resultsof the performance to the requesting device. However, if at 3832, thereis a mixture of programming languages is used among the retrieved mostrecent versions of task routines, then at 3836, the processor mayretrieve each of the one or more data sets specified by the one or moredata object identifiers from the one or more federated areas to whichthe requesting device and/or a user of the requesting device has beengranted access, and may then use the retrieved job flow definition, theretrieved newest versions of task routines, and the retrieved one ormore data sets to perform the job flow, but may do so using acombination of multiple different runtime interpreters and/or compilersto execute the executable instructions within each of those taskroutines. At 3838, the processor may then transmit the results of theperformance to the requesting device.

However, if at 3830, the processor successfully locates such an instancelog (during the search at 3824), then the processor may additionallydetermine at 3840 whether there is more than one such instance log, eachof which is associated with a different performance of the job flow withthe one or more data sets specified in the request. If only one suchinstance log is located at 3840, then at 3850, the processor may thenretrieve the versions specified in the instance log of each of the taskroutines for each task specified in the job flow definition by a flowtask identifier from the one or more federated areas to which therequesting device and/or a user of the requesting device has beengranted access. However, if at 3840, there is more than one suchinstance log located, then the processor may analyze the multipleinstance logs to identify and select the instance log from among themultiple instance logs that is associated with the most recentperformance of the job flow at 3842, before proceeding to retrievespecified versions task routines for each task of the job flow at 3850.

At 3852, for each task specified in the job flow definition, theprocessor may compare the retrieved version of the task routineidentified in the instance log to the newest version stored within theone or more federated areas to which the requesting device and/or a userof the requesting device has been granted access to determine whethereach of the retrieved task routines is the newest version. At 3860, ifeach of the retrieved task routines is the newest version thereof, thenthere is no need to perform the job flow anew, as the most recentprevious performance (or the only previous performance) already used thenewest version of each task routine such that the result reportgenerated is already the most up to date form of the result report,possible. Thus, at 3862, the processor may retrieve the result report ofthat previous performance using the result report identifier specifiedby the instance log from the one or more federated areas to which therequesting device and/or a user of the requesting device has beengranted access, and may then transmit the result report to therequesting device at 3734.

However, if at 3860, one or more of the task routines specified in theinstance log and retrieved from the one or more federated areas to whichthe requesting device and/or a user of the requesting device has beengranted access is not the newest version thereof, then at 3870, theprocessor may parse the job flow set forth in the job flow definition toidentify the earliest task within the job flow at which the version ofthe task routine so retrieved is not the newest version. At 3872, theprocessor may then check whether all of the newest versions of taskroutines, starting with the task routine for the identified earliesttask, proceeding through the task routines for each of the later tasksin the job flow, are written in the same programming language.

If, at 3872, all such retrieved newest task routines are written in thesame programming language, then at 3874, starting at the identifiedearliest task, the processor may use the newest version of task routinefor that task and for each later task in the job flow to perform thattask and each of the later tasks, thereby taking advantage of the one ormore earlier tasks of job flow at which the newest version of taskroutine was used in the most recent previous performance (or the onlyprevious performance). In so doing, the processor may be caused to usethe same runtime interpreter or compiler to execute the executableinstructions within all of such retrieved most recent versions of taskroutines. The processor may then transmit the result report generated insuch a partial performance of the job flow to the requesting device at3878. However, if at 3872, there is a mixture of programming languagesis used among these particular most recent versions of task routines,then at 3876, the processor may use the newest version of task routinefor that earliest identified task and for each later task in the jobflow to perform that task and each of the later tasks, but may do sousing a combination of multiple different runtime interpreters and/orcompilers to execute the executable instructions within each of thosetask routines. The processor may then transmit the result reportgenerated in such a partial performance of the job flow to therequesting device at 3878.

FIGS. 32A, 32B, 32C, 32D, 32E, 32F and 32G, together, illustrate anexample embodiment of a logic flow 4100. The logic flow 4100 may berepresentative of some or all of the operations executed by one or moreembodiments described herein. More specifically, the logic flow 4100 mayillustrate operations performed by the processor 2550 in executing thecontrol routine 2540, and/or performed by other component(s) of at leastone of the federated devices 2500.

At 4110, a processor of a federated device of a distributed processingsystem (e.g., at least one processor 2550 of one of the federateddevices 2500 of the distributed processing system 2000) may receive arequest from a requesting device, via a network (e.g., one of thereviewing devices 2800 via the network 2999) and through a portalprovided by the processor, that entails a performance of a job flow withone or more data sets as inputs thereto (e.g. one or more of the flowinput data sets 2330). The request may be explicitly for a performanceof the job flow, or may be for a repeat of a particular past performanceof the job flow, etc. The request may use any of a variety of objectidentifiers to identify any of a variety of particular data objects, jobflow definitions, instance logs, etc. for use in the performance.

At 4112, at least in embodiments in which the request is received at afederated device that controls access to the federated area specified inthe request, the processor may perform a check of whether the request isfrom an authorized device and/or from an authorized person or entity(e.g., scholastic, governmental or business entity) operating the devicethat is an authorized user of the specified federated area, and/or hasbeen granted a level of access that includes the authorization to havesuch requests acted upon. As has been discussed, the processor mayrequire the receipt of one or more security credentials from devicesfrom which requests are received. If, at 4112, the processor determinesthat the request is not from a device and/or user authorized to makesuch a request, then the processor may transmit an indication of denialof the request to the requesting device at 4114.

However, if at 4112, the processor determines that the request toprovide a federated area package is authorized, then at 4120, theprocessor may use the received identifiers to retrieve the variousobjects specified in the request from the one or more federated areas towhich access is authorized for the requesting device and/or for the userof the requesting device.

If, at 4120, the request includes a request to repeat a specificprevious performance of the job flow, then there may be no need toexecute GUI instructions that may be included in the job flowdefinition, and the processor may proceed to a check of programminglanguages at 4130. However, if at 4120, the request does not include arequest to repeat a specific previous performance, then at 4122, theprocessor may check whether the job flow definition includes GUIinstructions. If so, then at 4124, the processor may execute the GUIinstructions (whether written in the primary language normally usedduring the performance of a job flow or written in a secondary languagethat is also supported for use during the performance of a job flow) toallow a user to specify any remaining objects to be used in performingthe job flow before proceeding to the check at 4130.

At 4130, if all of the task routines retrieved for use in theperformance of the job flow are written in the primary programminglanguage, then the processor may perform the job flow at 4132 with theretrieved job flow definition, task routines and any flow input datasets. However, if at 4130, there is a mixture of programming languagesused in the executable instructions within the retrieved task routines,then the processor may instantiate a shared memory space at 4136. As hasbeen explained, there may be a primary programming language that may beexpected to be used in writing the executable instructions within thetask routines that may be used in the performance of a job flow. Such aprimary programming language may have been specifically created tobetter enable many-task computing using distributed processing, and maybe deemed the preferred programming language. However, as has also beendiscussed, to enable collaborations with developers who are not familiarwith the primary programming language and/or many-task computingprinciples, it may be deemed desirable to accommodate one or moresecondary programming languages that they may be familiar with. As aresult, there may be a mixture of programming languages used in writingthe executable instructions among a set of task routines that have beenretrieved for use in performing a job flow.

As will be familiar to those skilled in the art, there may bedifferences among those programming languages in how values withinarrays and/or other data structures may be organized and/or accessed(e.g., differences in support data types for data values, differences inindexing schemes, etc.). Thus, it may be that a mid-flow data set outputby one task routine written in one programming language needs to be putthrough a conversion of formatting, indexing and/or othercharacteristics before it can be provided as an input to another taskroutine written in another programming language. Among such conversionsmay be serialization and/or de-serialization to resolve differencesamong task routines as to how data within array structures of data setsmay be accessed. As has also been previously discussed, where a data setis put through such a conversion, it may be deemed desirable to storeeither the form of the data set prior to the conversion or the form ofthe data set after the conversion (but not both) in a federated area tothereby persist it such that it remains available for a futureevaluation of the performance of the job flow for sake ofaccountability. The form of such data that is not to be persisted bybeing stored in federated area(s) may be temporarily stored in a sharedmemory space that remains instantiated for the duration of theperformance of the job flow.

At 4140, for any task routine written in the primary programminglanguage that receives only flow input data set(s) as input, theprocessor may execute the executable instructions thereof to generatemid-flow data set(s) and/or result report(s) in a form that may bepersisted by being stored within federated area(s). The processor may doso at least partially in parallel with the execution of instructions ofother task routine(s) as the job flow and opportunities for parallelismpermit.

At 4142, the processor may serialize any flow input data set that isreceived as an input to a task routine written in a secondaryprogramming language, and may store such serialized forms of such flowinput data set(s) within the shared memory space, since such flow inputdata sets will have already been persisted in federated area(s). At4144, for any task routine written with executable instructions writtenin the secondary programming language that receives only one or more ofthese serialized flow input data sets as input, the processor mayexecute the executable instructions thereof to generate mid-flow dataset(s) and/or result report(s) in serialized form, which the processormay store in shared memory space to await de-serialization. Theprocessor may do so at least partially in parallel with execution ofinstructions of other task routine(s) as the job flow and opportunitiesfor parallelism permit (e.g., at least partially in parallel with theexecution of executable instructions written in the primary programminglanguage at 4140). At 4146, the processor may de-serialize each of thoseserialized forms of result reports and/or mid-flow data sets storedwithin the shared memory space to generate de-serialized forms thereofto be persisted in federated area(s). At 4148, the processor may thendelete, from shared memory space, any serialized form of flow input dataset not still required as input to a task routine, along with anyserialized form of result report that is also not required as input to atask routine.

At 4150, for any task routine written in the primary programminglanguage that receives, as its input, mid-flow input data set(s) and/orresult report(s) generated by other task routine(s) only in persistedform as stored within federated area(s), the processor may execute theexecutable instructions thereof to generate more mid-flow data set(s)and/or result report(s) in persisted form and stored within federatedarea(s). The processor may do so at least partially in parallel with theexecution of instructions of other task routine(s) as the job flow andopportunities for parallelism permit (e.g., at least partially inparallel with the execution of instructions written in either of theprimary or secondary programming languages at 4140 and/or 4144).

At 4152, for any task routine written in the secondary programminglanguage that receives, as input, mid-flow input data set(s) and/orresult report(s) generated by other task routine(s) only in serializedform within shared memory space, the processor may execute theexecutable instructions thereof to generate more mid-flow data set(s)and/or result report(s) in serialized form and stored in the sharedmemory space. The processor may do so at least partially in parallelwith the execution of instructions of other task routine(s) as the jobflow and opportunities for parallelism permit (e.g., at least partiallyin parallel with the execution of instructions written in either of theprimary or secondary programming languages at 4140, 4144 and/or 4150).At 4154, the processor may de-serialize each of those serialized formsof result reports and/or mid-flow data sets stored within the sharedmemory space to generate de-serialized forms thereof to be persisted infederated area(s).

At 4156, following the execution of instructions within task routines ateach of 4150 and 4152, the processor may then delete, from the sharedmemory space, any serialized form of flow input data set and/or mid-flowdata set not still required as input to a task routine, along with anyserialized form of result report that is also not required as input to atask routine.

At 4160, the processor may serialize any mid-flow data set or resultreport generated in non-serialized form (and persisted in a federatedarea) by a task routine with executable instructions written in theprimary language, and which is to be received as an input to other taskroutine(s) with executable instructions written in the secondaryprogramming language to generate serialized forms thereof that arestored within the shared memory space. At 4162, for any task routinewritten in the secondary programming language that receives, as input,mid-flow data set(s) and/or result report(s) that have been serializedfrom the persisted form generated by other task routine(s), theprocessor may execute the executable instructions thereof to generatemore mid-flow data set(s) and/or result report(s) in serialized form andstored within the shared memory space. The processor may do so at leastpartially in parallel with the execution of instructions of other taskroutine(s) as the job flow and opportunities for parallelism permit(e.g., at least partially in parallel with the execution of instructionswritten in either of the primary or secondary programming languages at4140, 4144, 4150 and/or 4152). At 4164, the processor may de-serializeeach of those any result reports and/or mid-flow data sets stored withinthe shared memory space to generate de-serialized forms thereof to bepersisted in federated area(s). At 4166, the processor may delete, fromthe shared memory space, any serialized form of flow input data setand/or mid-flow data set not still required as input to a task routine,along with any serialized form of result report that is also notrequired as input to a task routine.

At 4170, the processor may de-serialize any mid-flow data set or resultreport generated in serialized form (and stored within the shared memoryspace) by a task routine written in the secondary programming language,and which is to be received as an input to other task routine(s) withexecutable instructions written in the primary programming language togenerate de-serialize forms thereof that are persisted within federatedarea(s). At 4172 for any task routine written in the primary programminglanguage that receives, as input, mid-flow data set(s) and/or resultreports that have been de-serialized from the serialized form generatedby other task routine(s), the processor may execute executableinstructions thereof to generate more mid-flow data set(s) and/or resultreport(s) in de-serialized form and persisted within federated area(s).The processor may do so at least partially in parallel with theexecution of instructions of other task routine(s) as the job flow andopportunities for parallelism permit (e.g., at least partially inparallel with the execution of instructions written in either of theprimary or secondary programming languages at 4140, 4144, 4150, 4152and/or 4162). At 4174, the processor may delete, from the shared memoryspace, any serialized form of flow input data set and/or mid-flow dataset not still required as input to a task routine, along with anyserialized form of result report that is also not required as input to atask routine.

At 4180, the processor may check whether there are more task routinesstill to be executed to perform more of the tasks of the job flow in theorder specified by the retrieved job flow definition. If so, then theprocessor may continue to execute task routines, serialize data and/orde-serialize data, starting again at one or more of 4150, 4152, 4160 and4170.

However, if at 4180, there are no more task routines associated with thejob flow to be executed, then the processor may un-instantiate theshared memory space at 4182, and may transmit the results of theperformance of the job flow to the requesting device at 4184.

In various embodiments, each of the processors 2150, 2550 and 2850 mayinclude any of a wide variety of commercially available processors.Further, one or more of these processors may include multipleprocessors, a multi-threaded processor, a multi-core processor (whetherthe multiple cores coexist on the same or separate dies), and/or amulti-processor architecture of some other variety by which multiplephysically separate processors are linked.

However, in a specific embodiment, the processor 2550 of each of the oneor more federated devices 1500 may be selected to efficiently performthe analysis of multiple instances of job flows at least partially inparallel. By way of example, the processor 2550 may incorporate asingle-instruction multiple-data (SIMD) architecture, may incorporatemultiple processing pipelines, and/or may incorporate the ability tosupport multiple simultaneous threads of execution per processingpipeline. Alternatively or additionally by way of example, the processor1550 may incorporate multi-threaded capabilities and/or multipleprocessor cores to enable parallel performances of the tasks of morethan job flow.

In various embodiments, each of the control routines 2140, 2540 and2840, including the components of which each is composed, may beselected to be operative on whatever type of processor or processorsthat are selected to implement applicable ones of the processors 2150,2550 and/or 2850 within each one of the devices 2100, 2500 and/or 2800,respectively. In various embodiments, each of these routines may includeone or more of an operating system, device drivers and/orapplication-level routines (e.g., so-called “software suites” providedon disc media, “applets” obtained from a remote server, etc.). Where anoperating system is included, the operating system may be any of avariety of available operating systems appropriate for the processors2150, 2550 and/or 2850. Where one or more device drivers are included,those device drivers may provide support for any of a variety of othercomponents, whether hardware or software components, of the devices2100, 2500 and/or 2800.

In various embodiments, each of the storages 2160, 2560 and 2860 may bebased on any of a wide variety of information storage technologies,including volatile technologies requiring the uninterrupted provision ofelectric power, and/or including technologies entailing the use ofmachine-readable storage media that may or may not be removable. Thus,each of these storages may include any of a wide variety of types (orcombination of types) of storage device, including without limitation,read-only memory (ROM), random-access memory (RAM), dynamic RAM (DRAM),Double-Data-Rate DRAM (DDR-DRAM), synchronous DRAM (SDRAM), static RAM(SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory, polymermemory (e.g., ferroelectric polymer memory), ovonic memory, phase changeor ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS)memory, magnetic or optical cards, one or more individual ferromagneticdisk drives, non-volatile storage class memory, or a plurality ofstorage devices organized into one or more arrays (e.g., multipleferromagnetic disk drives organized into a Redundant Array ofIndependent Disks array, or RAID array). It should be noted thatalthough each of these storages is depicted as a single block, one ormore of these may include multiple storage devices that may be based ondiffering storage technologies. Thus, for example, one or more of eachof these depicted storages may represent a combination of an opticaldrive or flash memory card reader by which programs and/or data may bestored and conveyed on some form of machine-readable storage media, aferromagnetic disk drive to store programs and/or data locally for arelatively extended period, and one or more volatile solid state memorydevices enabling relatively quick access to programs and/or data (e.g.,SRAM or DRAM). It should also be noted that each of these storages maybe made up of multiple storage components based on identical storagetechnology, but which may be maintained separately as a result ofspecialization in use (e.g., some DRAM devices employed as a mainstorage while other DRAM devices employed as a distinct frame buffer ofa graphics controller).

However, in a specific embodiment, the storage 2560 in embodiments inwhich the one or more of the federated devices 2500 provide federatedspaces 2566, or the storage devices 2600 in embodiments in which the oneor more storage devices 2600 provide federated spaces 2566, may beimplemented with a redundant array of independent discs (RAID) of a RAIDlevel selected to provide fault tolerance to objects stored within thefederated spaces 2566.

In various embodiments, each of the input devices 2110 and 2810 may eachbe any of a variety of types of input device that may each employ any ofa wide variety of input detection and/or reception technologies.Examples of such input devices include, and are not limited to,microphones, remote controls, stylus pens, card readers, finger printreaders, virtual reality interaction gloves, graphical input tablets,joysticks, keyboards, retina scanners, the touch input components oftouch screens, trackballs, environmental sensors, and/or either camerasor camera arrays to monitor movement of persons to accept commandsand/or data provided by those persons via gestures and/or facialexpressions.

In various embodiments, each of the displays 2180 and 2880 may each beany of a variety of types of display device that may each employ any ofa wide variety of visual presentation technologies. Examples of such adisplay device includes, and is not limited to, a cathode-ray tube(CRT), an electroluminescent (EL) panel, a liquid crystal display (LCD),a gas plasma display, etc. In some embodiments, the displays 2180 and/or2880 may each be a touchscreen display such that the input devices 2110and/or 2810, respectively, may be incorporated therein astouch-sensitive components thereof.

In various embodiments, each of the network interfaces 2190, 2590 and2890 may employ any of a wide variety of communications technologiesenabling these devices to be coupled to other devices as has beendescribed. Each of these interfaces includes circuitry providing atleast some of the requisite functionality to enable such coupling.However, each of these interfaces may also be at least partiallyimplemented with sequences of instructions executed by correspondingones of the processors (e.g., to implement a protocol stack or otherfeatures). Where electrically and/or optically conductive cabling isemployed, these interfaces may employ timings and/or protocolsconforming to any of a variety of industry standards, including withoutlimitation, RS-232C, RS-422, USB, Ethernet (IEEE-802.3) or IEEE-1394.Where the use of wireless transmissions is entailed, these interfacesmay employ timings and/or protocols conforming to any of a variety ofindustry standards, including without limitation, IEEE 802.11a,802.11ad, 802.11ah, 802.11ax, 802.11b, 802.11g, 802.16, 802.20 (commonlyreferred to as “Mobile Broadband Wireless Access”); Bluetooth; ZigBee;or a cellular radiotelephone service such as GSM with General PacketRadio Service (GSM/GPRS), CDMA/1×RTT, Enhanced Data Rates for GlobalEvolution (EDGE), Evolution Data Only/Optimized (EV-DO), Evolution ForData and Voice (EV-DV), High Speed Downlink Packet Access (HSDPA), HighSpeed Uplink Packet Access (HSUPA), 4G LTE, etc.

However, in a specific embodiment, one or more of the network interfaces2190, 2590 and/or 2890 may be implemented with multiple copper-based orfiber-optic based network interface ports to provide redundant and/orparallel pathways in exchanging one or more of the data sets 2330 and/or2370.

In various embodiments, the division of processing and/or storageresources among the federated devices 1500, and/or the API architecturesemployed to support communications between the federated devices andother devices may be configured to and/or selected to conform to any ofa variety of standards for distributed processing, including withoutlimitation, IEEE P2413, AliJoyn, IoTivity, etc. By way of example, asubset of API and/or other architectural features of one or more of suchstandards may be employed to implement the relatively minimal degree ofcoordination described herein to provide greater efficiency inparallelizing processing of data, while minimizing exchanges ofcoordinating information that may lead to undesired instances ofserialization among processes. However, it should be noted that theparallelization of storage, retrieval and/or processing of portions ofthe data sets 2330 and/or 2370 are not dependent on, nor constrained by,existing API architectures and/or supporting communications protocols.More broadly, there is nothing in the manner in which the data sets 2330and/or 2370 may be organized in storage, transmission and/ordistribution via the network 2999 that is bound to existing APIarchitectures or protocols.

Some systems may use Hadoop®, an open-source framework for storing andanalyzing big data in a distributed computing environment. Some systemsmay use cloud computing, which can enable ubiquitous, convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, servers, storage, applications and services)that can be rapidly provisioned and released with minimal managementeffort or service provider interaction. Some grid systems may beimplemented as a multi-node Hadoop® cluster, as understood by a personof skill in the art. Apache™ Hadoop® is an open-source softwareframework for distributed computing.

The invention claimed is:
 1. An apparatus comprising a processor and astorage to store instructions that, when executed by the processor,cause the processor to perform operations comprising: receive, at theprocessor and from a remote device, a request to perform a job flowdefined in a job flow definition stored in at least one federated area,wherein: the job flow definition specifies a set of tasks to beperformed via execution of a corresponding set of task routines duringthe job flow performance; at least one flow input data set is to beemployed as an input to the job flow performance; at least one mid-flowdata set is to be exchanged between at least two of the set of taskroutines; at least one result report is to be output during the job flowperformance; and the at least one federated area is maintained within atleast one storage device to store the job flow definition, and multipletask routines, data sets and result reports; retrieve, from among themultiple task routines, a most recent version of each task routine ofthe set of task routines to perform a corresponding task of the set oftasks when executed; analyze each interface of each task routine of theset of task routines by which a data set is accepted as an input or isoutput during execution of the task routine to identify at least onedependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in different programminglanguages; execute the executable instructions of the set of taskroutines to perform the set of tasks to thereby perform the job flow; inresponse to having identified at least one dependency in which the firsttask routine outputs a mid-flow data set that the second task routineaccepts as an input, and in which the first task routine and the secondtask routine include executable instructions written in differentprogramming languages, perform operations comprising: instantiate ashared memory space to store at least one mid-flow data set during thejob flow performance; for each identified dependency of the at least oneidentified dependency: convert the mid-flow data set from a first formsupported by the programming language in which the executableinstructions of the first task routine are written, and into a secondform supported by the programming language in which the executableinstructions of the second task routine are written; store one of thefirst form and the second form of the mid-flow data set within the atleast one federated area as one of the multiple data sets; and storeanother of the first form and the second form of the mid-flow data setwithin the shared memory space as the mid-flow data set is converted;un-instantiate the shared memory space; and transmit the at least oneresult report output during the performance of the job flow to theremote device.
 2. The apparatus of claim 1, wherein: in a dependency ofthe at least one identified dependency, a selected one of theprogramming language in which the executable instructions of the firsttask routine are written and the programming language in which theexecutable instructions of the second task routine are written isdesignated as a primary programming language, and the non-selected oneis designated as a secondary programming language; and the multiple datasets and result reports are stored in the at least one federated area inthe one of the first form and the second form that is supported by theprimary programming language.
 3. The apparatus of claim 2, wherein theprocessor is caused to perform operations comprising: analyze eachinterface of each task routine of the set of task routines to identifyat least one other dependency among at least two task routines in whicha first task routine of the at least two task routines outputs amid-flow data set that a second task routine of the at least two taskroutines accepts as an input, and in which the first task routine andthe second task routine include executable instructions written in thesame programming language; and in response to having identified at leastone other dependency in which the first task routine outputs a mid-flowdata set that the second task routine accepts as an input, and in whichthe first task routine and the second task routine include executableinstructions written in the same programming language, performoperations comprising: for each identified dependency of the at leastone other identified dependency: refrain from converting the mid-flowdata set between the first form and the second form; analyze the form ofthe mid-flow data set to determine whether it comprises the one of thefirst form and the second form that is supported by the primaryprogramming language; and in response to a determination that the formof the mid-flow data set comprises the one of the first form and thesecond form that is supported by the primary programming language, storethe mid-flow data set within the at least one federated area as one ofthe multiple data sets.
 4. The apparatus of claim 2, wherein, inresponse to having identified at least one dependency in which the firsttask routine outputs a mid-flow data set that the second task routineaccepts as an input, and in which the first task routine and the secondtask routine include executable instructions written in differentprogramming languages, the processor is caused to perform operationscomprising: for each identified dependency of the at least oneidentified dependency: store the one of the first form and the secondform of the mid-flow data set within the at least one federated area asone of the multiple data sets based on which of the first form and thesecond form is supported by the primary programming language; and storeanother of the first form and the second form of the mid-flow data setthat is supported by the secondary programming language within theshared memory space as the mid-flow data set is converted.
 5. Theapparatus of claim 2, wherein one of the primary programming languageand the secondary programming language is selected from a groupconsisting of: SAS programming language; Python; JSON; Pascal; Fortran;BASIC; C; C++; R; and CUDA.
 6. The apparatus of claim 1, wherein theconversion of the mid-flow data set for each identified dependency ofthe at least one identified dependency comprises a conversion selectedfrom a group consisting of: a change between data types; a changebetween byte orderings; a change between delimiters separating datavalues; a change between big Endian and little Endian; a change betweenbyte widths of data values; a change in encoding of data values; areordering of data values between starting with a highest index valueand starting with a lowest index value; a change between a row-columnorganization and a column-row organization; a serialization fromstructured data to un-structured data; a de-serialization fromunstructured data to structured data; a serialization from an array tocomma-separated variables; and a de-serialization from comma-separatedvariables to an array.
 7. The apparatus of claim 1, wherein theprocessor is caused to perform operations comprising: for each taskroutine of the set of task routines that includes executableinstructions written in a first programming language, execute a firstruntime interpreter or compiler to execute, by the processor, theexecutable instructions written in the first programming language; andfor each task routine of the set of task routines that includesexecutable instructions written in a second programming language,execute a second runtime interpreter or compiler to execute, by theprocessor, the executable instructions written in the second programminglanguage.
 8. The apparatus of claim 1, wherein the processor is causedto perform operations comprising: receive, at the processor, a taskroutine from another device; retrieve a flow task identifier from thereceived task routine that identifies the task that the received taskroutine performs when the executable instructions of the received taskroutine are executed; analyze each task routine of the multiple taskroutines to identify at least one task routine of the multiple taskroutines that performs the same task when the executable instructions ofthe at least one task routine are executed; in response to identifyingat least one other task routine of the multiple task routines thatperforms the same task, perform operations comprising: analyze thereceived task routine to identify the programming language in which theexecutable instructions are written; analyze each task routine of the atleast one task routine to identify the programming language in which theexecutable instructions of each are written; for the received taskroutine and for each task routine of the at least one task routine,select an intermediate translator based on the programming language inwhich the executable instructions are written, and translate a portionof the executable instructions that implements the interface into anintermediate representation; compare the intermediate representationsgenerated from the executable instructions of the received task routineand each task routine of the at least one task routine to determine ifthere is a match; and in response to a determination that there is amatch, store the received task routine among the multiple task routinesin the at least one federated area.
 9. The apparatus of claim 8, whereinthe processor is caused to, in response to a determination that there isnot a match, perform operations comprising: generate a directed acyclicgraph (DAG) that depicts a difference between the interface of thereceived task routine and the interface of the at least one taskroutine; and transmit the DAG to the other device.
 10. The apparatus ofclaim 8, wherein each intermediate representation comprises executableinstructions written in an intermediate programming language.
 11. Acomputer-program product tangibly embodied in a non-transitorymachine-readable storage medium, the computer-program product includinginstructions operable to cause a processor to perform operationscomprising: receive, at the processor and from a remote device, arequest to perform a job flow defined in a job flow definition stored inat least one federated area, wherein: the job flow definition specifiesa set of tasks to be performed via execution of a corresponding set oftask routines during the job flow performance; at least one flow inputdata set is to be employed as an input to the job flow performance; atleast one mid-flow data set is to be exchanged between at least two ofthe set of task routines; at least one result report is to be outputduring the job flow performance; and the at least one federated area ismaintained within at least one storage device to store the job flowdefinition, and multiple task routines, data sets and result reports;retrieve, from among the multiple task routines, a most recent versionof each task routine of the set of task routines to perform acorresponding task of the set of tasks when executed; analyze eachinterface of each task routine of the set of task routines by which adata set is accepted as an input or is output during execution of thetask routine to identify at least one dependency among at least two taskroutines in which a first task routine of the at least two task routinesoutputs a mid-flow data set that a second task routine of the at leasttwo task routines accepts as an input, and in which the first taskroutine and the second task routine include executable instructionswritten in different programming languages; execute the executableinstructions of the set of task routines to perform the set of tasks tothereby perform the job flow; in response to having identified at leastone dependency in which the first task routine outputs a mid-flow dataset that the second task routine accepts as an input, and in which thefirst task routine and the second task routine include executableinstructions written in different programming languages, performoperations comprising: instantiate a shared memory space to store atleast one mid-flow data set during the job flow performance; for eachidentified dependency of the at least one identified dependency: convertthe mid-flow data set from a first form supported by the programminglanguage in which the executable instructions of the first task routineare written, and into a second form supported by the programminglanguage in which the executable instructions of the second task routineare written; store one of the first form and the second form of themid-flow data set within the at least one federated area as one of themultiple data sets; and store another of the first form and the secondform of the mid-flow data set within the shared memory space as themid-flow data set is converted; un-instantiate the shared memory space;and transmit the at least one result report output during theperformance of the job flow to the remote device.
 12. Thecomputer-program product of claim 11, wherein: in a dependency of the atleast one identified dependency, a selected one of the programminglanguage in which the executable instructions of the first task routineare written and the programming language in which the executableinstructions of the second task routine are written is designated as aprimary programming language, and the non-selected one is designated asa secondary programming language; and the multiple data sets and resultreports are stored in the at least one federated area in the one of thefirst form and the second form that is supported by the primaryprogramming language.
 13. The computer-program product of claim 12,wherein the processor is caused to perform operations comprising:analyze each interface of each task routine of the set of task routinesto identify at least one other dependency among at least two taskroutines in which a first task routine of the at least two task routinesoutputs a mid-flow data set that a second task routine of the at leasttwo task routines accepts as an input, and in which the first taskroutine and the second task routine include executable instructionswritten in the same programming language; and in response to havingidentified at least one other dependency in which the first task routineoutputs a mid-flow data set that the second task routine accepts as aninput, and in which the first task routine and the second task routineinclude executable instructions written in the same programminglanguage, perform operations comprising: for each identified dependencyof the at least one other identified dependency: refrain from convertingthe mid-flow data set between the first form and the second form;analyze the form of the mid-flow data set to determine whether itcomprises the one of the first form and the second form that issupported by the primary programming language; and in response to adetermination that the form of the mid-flow data set comprises the oneof the first form and the second form that is supported by the primaryprogramming language, store the mid-flow data set within the at leastone federated area as one of the multiple data sets.
 14. Thecomputer-program product of claim 12, wherein, in response to havingidentified at least one dependency in which the first task routineoutputs a mid-flow data set that the second task routine accepts as aninput, and in which the first task routine and the second task routineinclude executable instructions written in different programminglanguages, the processor is caused to perform operations comprising: foreach identified dependency of the at least one identified dependency:store the one of the first form and the second form of the mid-flow dataset within the at least one federated area as one of the multiple datasets based on which of the first form and the second form is supportedby the primary programming language; and store another of the first formand the second form of the mid-flow data set that is supported by thesecondary programming language within the shared memory space as themid-flow data set is converted.
 15. The computer-program product ofclaim 12, wherein one of the primary programming language and thesecondary programming language is selected from a group consisting of:SAS programming language; Python; JSON; Pascal; Fortran; BASIC; C; C++;R; and CUDA.
 16. The computer-program product of claim 11, wherein theconversion of the mid-flow data set for each identified dependency ofthe at least one identified dependency comprises a conversion selectedfrom a group consisting of: a change between data types; a changebetween byte orderings; a change between delimiters separating datavalues; a change between big Endian and little Endian; a change betweenbyte widths of data values; a change in encoding of data values; areordering of data values between starting with a highest index valueand starting with a lowest index value; a change between a row-columnorganization and a column-row organization; a serialization fromstructured data to un-structured data; a de-serialization fromunstructured data to structured data; a serialization from an array tocomma-separated variables; and a de-serialization from comma-separatedvariables to an array.
 17. The computer-program product of claim 11,wherein the processor is caused to perform operations comprising: foreach task routine of the set of task routines that includes executableinstructions written in a first programming language, execute a firstruntime interpreter or compiler to execute, by the processor, theexecutable instructions written in the first programming language; andfor each task routine of the set of task routines that includesexecutable instructions written in a second programming language,execute a second runtime interpreter or compiler to execute, by theprocessor, the executable instructions written in the second programminglanguage.
 18. The computer-program product of claim 11, wherein theprocessor is caused to perform operations comprising: receive, at theprocessor, a task routine from another device; retrieve a flow taskidentifier from the received task routine that identifies the task thatthe received task routine performs when the executable instructions ofthe received task routine are executed; analyze each task routine of themultiple task routines to identify at least one task routine of themultiple task routines that performs the same task when the executableinstructions of the at least one task routine are executed; in responseto identifying at least one other task routine of the multiple taskroutines that performs the same task, perform operations comprising:analyze the received task routine to identify the programming languagein which the executable instructions are written; analyze each taskroutine of the at least one task routine to identify the programminglanguage in which the executable instructions of each are written; forthe received task routine and for each task routine of the at least onetask routine, select an intermediate translator based on the programminglanguage in which the executable instructions are written, and translatea portion of the executable instructions that implements the interfaceinto an intermediate representation; compare the intermediaterepresentations generated from the executable instructions of thereceived task routine and each task routine of the at least one taskroutine to determine if there is a match; and in response to adetermination that there is a match, store the received task routineamong the multiple task routines in the at least one federated area. 19.The computer-program product of claim 18, wherein the processor iscaused to, in response to a determination that there is not a match,perform operations comprising: generate a directed acyclic graph (DAG)that depicts a difference between the interface of the received taskroutine and the interface of the at least one task routine; and transmitthe DAG to the other device.
 20. The computer-program product of claim18, wherein each intermediate representation comprises executableinstructions written in an intermediate programming language.
 21. Acomputer-implemented method comprising: receiving, by a processor, andfrom a remote device, a request to perform a job flow defined in a jobflow definition stored in at least one federated area, wherein: the jobflow definition specifies a set of tasks to be performed via executionof a corresponding set of task routines during the job flow performance;at least one flow input data set is to be employed as an input to thejob flow performance; at least one mid-flow data set is to be exchangedbetween at least two of the set of task routines; at least one resultreport is to be output during the job flow performance; and the at leastone federated area is maintained within at least one storage device tostore the job flow definition, and multiple task routines, data sets andresult reports; retrieving, from among the multiple task routines, amost recent version of each task routine of the set of task routines toperform a corresponding task of the set of tasks when executed;analyzing, by the processor, each interface of each task routine of theset of task routines by which a data set is accepted as an input or isoutput during execution of the task routine to identify at least onedependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in different programminglanguages; executing, by the processor the executable instructions ofthe set of task routines to perform the set of tasks to thereby performthe job flow; in response to having identified at least one dependencyin which the first task routine outputs a mid-flow data set that thesecond task routine accepts as an input, and in which the first taskroutine and the second task routine include executable instructionswritten in different programming languages, performing operationscomprising: instantiating, by the processor, a shared memory space tostore at least one mid-flow data set during the job flow performance;for each identified dependency of the at least one identifieddependency: converting, by the processor, the mid-flow data set from afirst form supported by the programming language in which the executableinstructions of the first task routine are written, and into a secondform supported by the programming language in which the executableinstructions of the second task routine are written; storing one of thefirst form and the second form of the mid-flow data set within the atleast one federated area as one of the multiple data sets; and storinganother of the first form and the second form of the mid-flow data setwithin the shared memory space as the mid-flow data set is converted;un-instantiating, by the processor, the shared memory space; andtransmitting, from the processor, the at least one result report outputduring the performance of the job flow to the remote device.
 22. Thecomputer-implemented method of claim 21, wherein: in a dependency of theat least one identified dependency, a selected one of the programminglanguage in which the executable instructions of the first task routineare written and the programming language in which the executableinstructions of the second task routine are written is designated as aprimary programming language, and the non-selected one is designated asa secondary programming language; and the multiple data sets and resultreports are stored in the at least one federated area in the one of thefirst form and the second form that is supported by the primaryprogramming language.
 23. The computer-implemented method of claim 22,comprising: analyzing, by the processor, each interface of each taskroutine of the set of task routines to identify at least one otherdependency among at least two task routines in which a first taskroutine of the at least two task routines outputs a mid-flow data setthat a second task routine of the at least two task routines accepts asan input, and in which the first task routine and the second taskroutine include executable instructions written in the same programminglanguage; and in response to having identified at least one otherdependency in which the first task routine outputs a mid-flow data setthat the second task routine accepts as an input, and in which the firsttask routine and the second task routine include executable instructionswritten in the same programming language, performing operationscomprising: for each identified dependency of the at least one otheridentified dependency: refraining from converting the mid-flow data setbetween the first form and the second form; analyzing, by the processor,the form of the mid-flow data set to determine whether it comprises theone of the first form and the second form that is supported by theprimary programming language; and in response to a determination thatthe form of the mid-flow data set comprises the one of the first formand the second form that is supported by the primary programminglanguage, storing the mid-flow data set within the at least onefederated area as one of the multiple data sets.
 24. Thecomputer-implemented method of claim 22, comprising, in response tohaving identified at least one dependency in which the first taskroutine outputs a mid-flow data set that the second task routine acceptsas an input, and in which the first task routine and the second taskroutine include executable instructions written in different programminglanguages, performing operations comprising: for each identifieddependency of the at least one identified dependency: storing the one ofthe first form and the second form of the mid-flow data set within theat least one federated area as one of the multiple data sets based onwhich of the first form and the second form is supported by the primaryprogramming language; and storing another of the first form and thesecond form of the mid-flow data set that is supported by the secondaryprogramming language within the shared memory space as the mid-flow dataset is converted.
 25. The computer-implemented method of claim 22,wherein one of the primary programming language and the secondaryprogramming language is selected from a group consisting of: SASprogramming language; Python; JSON; Pascal; Fortran; BASIC; C; C++; R;and CUDA.
 26. The computer-implemented method of claim 21, wherein theconversion of the mid-flow data set for each identified dependency ofthe at least one identified dependency comprises a conversion selectedfrom a group consisting of: a change between data types; a changebetween byte orderings; a change between delimiters separating datavalues; a change between big Endian and little Endian; a change betweenbyte widths of data values; a change in encoding of data values; areordering of data values between starting with a highest index valueand starting with a lowest index value; a change between a row-columnorganization and a column-row organization; a serialization fromstructured data to un-structured data; a de-serialization fromunstructured data to structured data; a serialization from an array tocomma-separated variables; and a de-serialization from comma-separatedvariables to an array.
 27. The computer-implemented method of claim 21,comprising: for each task routine of the set of task routines thatincludes executable instructions written in a first programminglanguage, executing, by the processor, a first runtime interpreter orcompiler to execute, by the processor, the executable instructionswritten in the first programming language; and for each task routine ofthe set of task routines that includes executable instructions writtenin a second programming language, executing, by the processor, a secondruntime interpreter or compiler to execute, by the processor, theexecutable instructions written in the second programming language. 28.The computer-implemented method of claim 21, comprising: receiving, atthe processor, a task routine from another device; retrieving a flowtask identifier from the received task routine that identifies the taskthat the received task routine performs when the executable instructionsof the received task routine are executed; analyzing, by the processor,each task routine of the multiple task routines to identify at least onetask routine of the multiple task routines that performs the same taskwhen the executable instructions of the at least one task routine areexecuted; in response to identifying at least one other task routine ofthe multiple task routines that performs the same task, performingoperations comprising: analyzing, by the processor, the received taskroutine to identify the programming language in which the executableinstructions are written; analyzing, by the processor, each task routineof the at least one task routine to identify the programming language inwhich the executable instructions of each are written; for the receivedtask routine and for each task routine of the at least one task routine,selecting, by the processor, an intermediate translator based on theprogramming language in which the executable instructions are written,and translate a portion of the executable instructions that implementsthe interface into an intermediate representation; comparing, by theprocessor, the intermediate representations generated from theexecutable instructions of the received task routine and each taskroutine of the at least one task routine to determine if there is amatch; and in response to a determination that there is a match, storingthe received task routine among the multiple task routines in the atleast one federated area.
 29. The computer-implemented method of claim28, comprising, in response to a determination that there is not amatch, performing operations comprising: generating, by the processor, adirected acyclic graph (DAG) that depicts a difference between theinterface of the received task routine and the interface of the at leastone task routine; and transmitting, from the processor, the DAG to theother device.
 30. The computer-implemented method of claim 28, whereineach intermediate representation comprises executable instructionswritten in an intermediate programming language.